{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Quickstart Guide: \n",
    "\n",
    "This Quickstart Guide presents a simple example of **ocean data challenge** for mapping the Sea Surface Height from sparse observations. \n",
    "\n",
    "The methodology is based on an Observing System Simulation Experiment (OSSE). The inputs data represent altimeter observations extracted from a realistic high-resolution ocean model simulation (NATL60). A simple mapping algorithm (Optimal Interpolation) is given as a baseline for the reconstructed SSH field from the sparse observations. Finally, a deep end-to-end learning approach is provided (Fablet et al., 2020): it already beats the OI (Beauchamp et al. 2020). Last, a comparison between the reconstructed OI, the reconstructed FP-GENN and the reference SSH fields is done to quantify the reconstruction scores.\n",
    "\n",
    "The notebook is structured as follows:\n",
    "\n",
    "    1) downloading the data\n",
    "    2) Setup configuration of the interpolation\n",
    "    3) Run the DINAE experiment\n",
    "    4) Plot some figures and interpolation scores\n",
    "\n",
    "This quickstart guide requires GPU capabilities activated to run."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Initializing DINAE libraries...\n",
      "...Done\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Using TensorFlow backend.\n"
     ]
    }
   ],
   "source": [
    "import sys\n",
    "sys.path.append(\"../\")\n",
    "from DINAE import *"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import logging\n",
    "logger = logging.getLogger()\n",
    "logger.setLevel(logging.INFO)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/anaconda/envs/py35/lib/python3.5/site-packages/distributed/bokeh/core.py:56: UserWarning: \n",
      "Port 8787 is already in use. \n",
      "Perhaps you already have a cluster running?\n",
      "Hosting the diagnostics dashboard on a random port instead.\n",
      "  warnings.warn('\\n' + msg)\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table style=\"border: 2px solid white;\">\n",
       "<tr>\n",
       "<td style=\"vertical-align: top; border: 0px solid white\">\n",
       "<h3>Client</h3>\n",
       "<ul>\n",
       "  <li><b>Scheduler: </b>tcp://127.0.0.1:35891\n",
       "  <li><b>Dashboard: </b><a href='http://127.0.0.1:40899/status' target='_blank'>http://127.0.0.1:40899/status</a>\n",
       "</ul>\n",
       "</td>\n",
       "<td style=\"vertical-align: top; border: 0px solid white\">\n",
       "<h3>Cluster</h3>\n",
       "<ul>\n",
       "  <li><b>Workers: </b>1</li>\n",
       "  <li><b>Cores: </b>1</li>\n",
       "  <li><b>Memory: </b>9.85 GB</li>\n",
       "</ul>\n",
       "</td>\n",
       "</tr>\n",
       "</table>"
      ],
      "text/plain": [
       "<Client: scheduler='tcp://127.0.0.1:35891' processes=1 cores=1>"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import dask\n",
    "cluster = dask.distributed.LocalCluster()\n",
    "cluster.scale(1)\n",
    "client = dask.distributed.Client(cluster)\n",
    "client"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 1- DOWNLOADING DATA"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "When downloading the 3 datasets (ref, data & oi), be sure that the names of the files will be the same than those specified in the config.yml file used to define the setup configuration. If no, please modify the config.yml file or change the downloaded file names."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Download Nature run SSH for mapping evaluation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "#!wget https://s3.eu-central-1.wasabisys.com/melody/ref.nc -O \"ref.nc\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Download Synthetic SSH observation for OI mapping"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "#!wget https://s3.eu-central-1.wasabisys.com/melody/data.nc -O \"data.nc\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#####  Download OI mapping"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "#!wget https://s3.eu-central-1.wasabisys.com/melody/oi.nc -O \"oi.nc\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2- SETUP CONFIGURATION "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# description of the parameters\n",
    "domain   = \"GULFSTREAM\"\n",
    "opt      = \"nadirswot\"\n",
    "lag      = \"0\"             \n",
    "type_obs = \"mod\"       # mod/obs\n",
    "\n",
    "# main code\n",
    "parser = argparse.ArgumentParser()\n",
    "with open('config.yml', 'rb') as f:\n",
    "    conf = yaml.load(f.read())\n",
    "    \n",
    "# list of global parameters (comments to add)\n",
    "fileMod                 = conf['path_files']['fileMod']\n",
    "fileOI                  = conf['path_files']['fileOI']\n",
    "fileObs                 = conf['path_files']['fileObs']\n",
    "flagTrWMissingData      = conf['data_options']['flagTrWMissingData'] \n",
    "flagloadOIData          = conf['data_options']['flagloadOIData']\n",
    "include_covariates      = conf['data_options']['include_covariates']\n",
    "lfile_cov               = conf['data_options']['lfile_cov']\n",
    "lname_cov               = conf['data_options']['lname_cov']\n",
    "lid_cov                 = conf['data_options']['lid_cov']   \n",
    "N_cov                   = ifelse(include_covariates==True,len(lid_cov),0)\n",
    "size_tw                 = conf['data_options']['size_tw'] \n",
    "Wsquare                 = conf['data_options']['Wsquare']\n",
    "Nsquare                 = conf['data_options']['Nsquare']\n",
    "DimAE                   = conf['NN_options']['DimAE']\n",
    "flagAEType              = conf['NN_options']['flagAEType']\n",
    "sigNoise                = conf['data_options']['sigNoise']\n",
    "flagTrOuputWOMissingData= conf['data_options']['flagTrOuputWOMissingData']\n",
    "stdMask                 = conf['data_options']['stdMask']\n",
    "dropout                 = conf['data_options']['dropout']\n",
    "start_eval_index        = conf['data_options']['start_eval_index']\n",
    "end_eval_index          = conf['data_options']['end_eval_index']\n",
    "start_train_index       = conf['data_options']['start_train_index']\n",
    "end_train_index         = conf['data_options']['end_train_index']\n",
    "wl2                     = conf['data_options']['wl2']\n",
    "batch_size              = conf['training_params']['batch_size']\n",
    "NbEpoc                  = conf['training_params']['NbEpoc']\n",
    "Niter                   = conf['training_params']['Niter']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3- CREATE OUTPUT DIRECTORY"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "if flagAEType==1:\n",
    "    suf1 = \"ConvAE\"\n",
    "else:\n",
    "    suf1 = \"GENN\"\n",
    "    \n",
    "if flagTrWMissingData==0:\n",
    "    suf2 = \"womissing\"  \n",
    "elif flagTrWMissingData==1:\n",
    "    suf2 = \"wmissing\"\n",
    "else:\n",
    "    suf2 = \"wwmissing\"\n",
    "    \n",
    "suf3 = \"FP\"\n",
    "suf4 = ifelse(include_covariates==True,\"w\"+'-'.join(lid_cov),\"wocov\")\n",
    "dirSAVE = '.'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 4- RUN EXPERIMENTS"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 4.1 Read the data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1) .... Load SSH dataset (training data): data.nc\n",
      ".... Load OI SSH dataset (training data): oi.nc\n",
      ".... Load OI dataset (training data): oi.nc\n",
      ".... # loaded samples: 275 \n",
      "10\n"
     ]
    },
    {
     "data": {
      "image/png": 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I0wfHD0xh1/sqr/SlMPmBwzC2diEOSXrqAm0nc2qjEG2E0ukI0u2JxYRwZoeNDoDF9FAd2eCSkSDnkUZPGNmXS0el0l5RYAo8DrDJVJUfacUYlKbwY8z8UmZ+mX1+K4DPM/M+AJ+3z0eOE79Z9YS4FEgTuCZ5CW5lVu2QiwDYydwmFGMMXkwDs47KpGOTlJiC09H2anAZkFRYZ6Ob9Oi1DKSk2nIxuDJtm0np+lAA8tz5L3ZPz1Q5KivAsMyHnwPwKfv4UwB+fkifsyzsem+lKVwKbIlUHBejqZe1BBhAjzGKMYYqCKoDPHZHH3+CrYw0ESuTT0nmKDIRFUE5U4IdA1ME1Q4FWrHAoEIiI2JO2JCp9U1UbeVWhkEIBQbwl0T0EBHdYI89xzagBYBvAXhO95uG1TauQoUKq8MghMIPMfO/APDTAN5CRC+PX2Tmvlw5w2obdzFU+QpLQMI+VdhFB2DbwplUHIuu+Wu+VaNo9g6x59CMfb/85kXTrtgmRAbiVm8ukQmIyqy7xoy1EcmNiCISBPj2dCq82TWbqbA8rFooMPPjdv8UgD+F9I580rWPs/unVvs5g8DxqQOVCXER7HpgGqpNSNoE3TShg1N0l+hxAz1ubEWjgqn3SlpOxLwwmTj/XLKT41+U1ORwjNPegikmYE8X56JbXTx/gu0o5QqmPGO0ocAEXTGvLBurbTA7TkRb3GMAr4D0jvwsgNfZ014H4M9W8zmDRGVjLo5SR+l24FDkRCoYOWXpEGUA0zQwNQP0SW82mZ3sGaOz3UDXZLzQfp58GTQo+Bc8KQstotW597jrJetDiF4XDaKcTNUtXCpcHKutKXsOgD+VXrNIAfxHZv4vRPQFAH9IRNcDmAXwS6v8nMGhEgqLQrVUSF9OARSudNoKgrpNYNKBGOHkjTf1Hcs0nDYg4cL2VdrWNoR8Am1zHHz0QAHstIUuAQAASUsO6CZbEwZefRDGaVc4tUgpd4UlYVVCgZmPA/iePsdPAfjx1Yw9LByfOoDJ90/j5L+vwpMxdr1vGkhhtQNAtchrDSazZCpt8rUHZCgkDLkxrGlGNgHJ1I1oHzXbg5IJpsYyuSnwKTjiV8meBBwZa3fK86N3StXlnkMzno0NCBmPpMlqDzaK4vInKuGwLFQ/VwUA8L4E2BBh3PORCvLFSiIclK+PKI1RkFC9m3Ae5cqWRRvfh9KN5TIaZdwgEMKAwL57+qv+jJAURfHBRc5dbJwKvbgsKSkqLaEXumlkEutII3D1InaCSw0EQEZ8CzEZChD8AGRkxYarjDQEKIlk6AkDysmv5h6xL8GRsS5S8qCK7vwH64tIUHY62rubiq7S6woXxWWpKew+UkUguqHaSqIGW3UoHnMNYG1FozgFyXMt9CBuA9dVqwDYMViiD9pWVjq+RcfO5HtNcqCC78Zjt035yc+JaB4mtVsSvYejMYvecSr0x2UpFI7vF79CxdAjmPzwYa8ViLZg/QFJmHgqt2q/q3LsCuPse0+gb/NqfCwcNDyngiNa9b5EFiHjBYMrsb5INJFTOc/5OzgJkQiXTenMGN/lusKScFkKBSDYyxXEqQgAZsx4piXHbeBCiy7nQBURI1MMglRQZvLYt5h3JoW2WoMmkHU4+tW9bkIUwURORjuRXTJUDJNZUpaIF9J1qeKU/etO69ENxp7DlV9hKbgsfQoAqtLaCC5/gKxPwdTZTl55nWzFIyvxBKqccPRA2Z/Qs6r7rtNWRlgnI2mA2XIo1IK24TIZPY17VFYd80U6BO0gCBHP35hCQqgRGzWn3Leas0IvLltNoUKFCv1x2QoFxzxc+RUgtQ019ozIVBDg6NRdy3nPkkR9bX3f9JWjMZ3ToJsgxTkqvafRUsFbZ6D3A1inZD+t7vj+oKk4HgXAnW8jEJp8KjQ0hWhKhYvisjUfHC53v8Ku903LxLXt4blmgJwsS5I9yRZDKeYyCavFnvulEaw/aucoRT6CwM1IIfzofvtY7XclCxHRazfDs/8Ym8UIRKZGxmCGJXC1QyQMumyXv+Xjsv+pTrztMs9ZMDaxKGNwZnznpXgD4BvFcsalCkfAHnMefpeARJJL4JuzuChnxiVb3ydAqeCXYBtW9JRtfRiegSA4dEMcpKZhZBzbuCa+flctOfnhitD1UrjshQKAy9or7dRsRPTopMspzF4w2ByEHgYrRlS6DH9XOcehkLyGld+1oQvmg7xkMvbNZqCCIPK1EN2g0L2Ka8b3gxBtg0vnxWZNhYujEgpYpCLvMsDkhw579ZsKVUo0ktZMJJsOfR8Wm5w+JyGai3FDWec3cGp97JdwjE5uLK8xdFVEduPEbx4Q4aGtYPHJVpYu3ppBzrcAjR5S2Aq9qIQCcNmuHo52DbYKUqoNVejB4Ca6hu8S3Y09h2YiZ4JF7HAk17CFyxmG8VhMvprS11zkFEhaIfvdR6Z7s1GtMPCCwGo5VITS71gwkEHlXL4EKqEA4OitU5elCeFXcgPfCi68GD2OVu++DVzti76vQ5+yZ18A1cWOJOOHEm2mkIzkMxtT8WP05Uxx5oozMZwgcynXsfBxr1+mi8BSUQkFh8sxWkUIXvqE7QRj7xfwJr+b0GlvMRknogU456Ccb7UDy6vmhIEwtgoHAyv2QiR0jpb3+DGdj8A5OOuyxTj5JjtW3JValUlWStmX1PW8Qg+qn8fhMhMKux6YDpPDOQLcamsnLFK7ucnaFYrcPTPdNenLm+/96AVCCC8enzrQe36kYfhek9ZfEAuRHlgh4j4D7lr8Y0ZMLVexb10clVCwOHZw6rLrEUCxeu21Bg7OuNg3kPTmC3BckejGcCtx7PzvMkX6X0z5/LiwytVNOL/Azo8e6n1vl+nDkaYTQqVkIxqMnR/pGqOCx2WfvBSjXz/ETYson4A0gSGrLMGGJwkhLGkjFLO/cXN5DJ8kxL5Biz/uJnmXECiNESVH+Y5P3cLEhktJk/dnULdgcf4QBogpNLN1H+Oux3E3Kntehb5YsVAgohcB+IPo0G4AbwewHcC/A+CaOdzOzH+x4iusUKHCmmLF5gMzP2Jbxb0UwPcBmIdQvAPAEffaRhII1737MjIfnGff2flOxS7Cqut8Cv71LsS9HGPuBc/ajOB49HZ+hBNvO4ATbzvgVfzS4m11fxcZIS1krCpHOZ8CwOwNN0vY0ZBcvxsi7vsQR0RcXkOFvhiU+fDjAI4x8yz16HYbB5eLRjn5gcPyz7OrRaDgL3ACoKAw66nXn7DrfdNSRKUgpKxAaaJJLwdGzKl2ycYsVkgJJZvNTEzsNSISBn0Km8hYEwiwjsU+4ytIApPLmajQF4NyNL4awO9Hz28koi8T0ScW6zi9HtvGPXbHFPZeBj0CnNMOsKFA51y0yUMAwDUTej/GAiKGTRzyNQbW21861UUMFktVBnyvB3mCstbAQeB4n2FBvU5hJ+AiQebhtBSbWekqNqsu5P2xaqFARDUAPwvgj+yhDwPYA+ClAJ4A0PeXH0XbuAoClxwUlzNzJkVRKEQFjzMCOWPM/ruDpTFMzRZRWaFBUfmyr3Vg8tmGUKLm94VjabJbCJXGFx2smlIhlXs55fBZzknqpIjrJaED07RPi75M0K+gbDEMQlP4aQD/yMxPAgAzP8nMmpkNgI9B2shtHGxitXLvvTPYe++MULlb5iIhNSWf3oxUqiWh4GsHujH5/ukQJuRQVVkKYTLEFLGfwRdJDjjxtgO+jLq7dRxUiBi4LfZZOJx8y01CMd8mn77tax/s5v0RjHIvyk2O3Ueme5i3L4ZBCIXXIDIdXA9Ji1+AtJHbMDh6yyY2IdzEMpZvMbfOOOtQDBNIbgu2FYjd4Mw2eUlcGzkqn5+y10Ioj7SFi8DXLTgLoKT+szdzOBYS3WNYjYNs74nE9rJQuQgKKoRaPnZUTn5w85dSm2WSy6y6lySAnwTwJ9Hh+4noK0T0ZQA/BmD/aj5jFDh6cHPmK3gN3aUVKylhdqsnp3ZSKwa1yZsS3aBceW+/EwLOVHCbExpM0o7uUqp6qQYDCMlULkISZ0haP0U/vwKMUMOrIlyLKuSY00JK1ZybvGpy8kOHF23ttxhWJRSYeY6Zr2Tms9GxX2Xm72Lm72bmn2XmJ1bzGaPAZg1NBodgYEE2mazwXqW2zkauCUcB10xv0pJ1KnphQhy0B/uap29jmcSXvDFtnUSYrPGFo2Q+eEKWrmiGFyxWOJT8B4iEgXNkcq9vokKV5twXmzE0uet90zCZCAHvCCRXMyAT19iIg3fMuZLneJwHpr2fwZkL3r/gHJfGfoaSprBLmXjHpw6U6ODlA1C+Q7syHrv/p2MHp8qZlF0+Dq9tuFO6xttsmPzAYZx88/K0BKASCn3x2B1T2Hf35tIWHN0aZ7L6S+PXUF1YWoUX8SUAwSyIE4CC2SHv944+18NhiSp6XPLs6OC9A9LVQrjLsqHPbq+6q7sgx7EQmyNub1Oe3XmbsWx+1/uml202OFS1D4thk2kLPfRkcSGUSxRg2z7OVkOefHOfECLDFkcZX4FIhSrlIZgMUAUjWZADurG05Tj2GcSJTGydoy5U6TSP7sIr+Z4AKYANQN0vOjlG7sQ4QWKTYRVmUaUpVKhQoYRKKCyCx26f6tuubCNC/ACqZPc7qnVqK9lyOc5Oi1isg5ZNFfZVhhRMCtUi2WwnJlOTbakxcj1hE6JqDNMw4IaGGdPgmhGmZhs6dW3t+9VkHDs4FSjl3eZqMnyWJLxj05kRmwW7HpjGrgemV8VSXgmFi2CxfgMbDaQlGpDMK7/JBFY+rp8sKKiWskVH1LcfhksLFj+EkdBlrmxGou0PaTeVW5/CMn7Dk2+6yTa2ZcAmUHkClcyAU9mQBB9Gv/E9U1TUZzL8GJGZ4gUGLyvjb71i1wPTOPHWAzjx1tW1LaiEwkXQc0NtUCQLNpvPhehs8lLScSs7lViXVae/luAdjPGxVIxXN46y+QsmY+gaL99kd1EPFx5lEsEQpy0zBXYoJZOhNEQfFii5fgTtAF3HNwMGtIZVjsaLYLUSd93AafrOkx/XFyBkAjpfIatFmuSQZDP68TpKCFaslhAzJSXzzsm4vEtVHeVTpjllUEuVwqbuOihX4jzV1KMtcMqAa03nvn+XcCr1lOjOoNyA2H1kGif2D+Z+rTSFS2Cj03ZNfuAwdMOyIUcJSwBE7Qe8V96Z2YtWM7rqyigUCQWQD0GGEKBuSvv65bJZma0FVItsaFOJEDIkwicPadMoKDIvymOceOuB0vf1laCOqzHuXGUFxkYmc909M13qrblabOCfYm1AYxu72SRPaOitGsWEhh5j6DGWrkpRHQS5FGDAVRf3YPL90yGfgeF9CWCA6wzdNCGZyToy9fjy42Kzr7/FTmiZwGQIXDc+pZozBmoGvDWXSV4zfYWYHg8ZlpwCpsEwdfF3cMLil3Cp2NbHsFH7QSw1D2SpqITCJUDJxs6DpcSI0y5jmKaWrWGgmwYmQWjxpiOfQx+oHLJKWxnp7Pm4rsHVJOhxLf0dV9jl2UVAuGFk7FQmOOpGNtu1KlDSM3Y+WNbouC7f09jr6CZ48dqDY5pGtN9A2HNoBsduGmytTiUULoETv3w7Jj99z6gvY0WY/PQ9YNf6DQi2tbJhvzHj+zfGGX/9VP5SmbUzI6LmtFBAckHJNifxv0X5Ey4BburQnXpMA7kCUumGjZyQTuRiNqQG6MgtrBbKt3I20Ql8EGSJYpx2FLE5eX+Ct502DvYcmsGxmwdfvFcJhSWAWxvYPW3ZjeEqEA15+4CJYVJYlRolWvUYe++bgbK2vO8HaTUFX/IMwDRZtjGzqkV39tcPAgSouQQ0nyA9n4TrZkLRSoXRuZX4GgdTL6s4R3/pzp5aCbh2dDmVqz+dzcTig5n8wAYppx6SYlMJhaVgg5bXsiFQamRFtSXRUBxi/9ZRx6k43kyKvquli+mrwoYrdXAoOqq17HSCZE4hmVNQ86u/rdQC+bJuPW6g5hJf5kjzSem7qI4kZvXkGlgNSLXleqig0FAm5UhboJ73rHfsOTQjBWBDQBWSXAJ6Soc3CJKagckVyBGVutXUrq7cScJiYz36R2/pvdFcuNI55USjkNXWlQ/oZqR+G6zYn+CgOhLmzC4QdG4lh5k7AAAgAElEQVQ7Vrs5rBhoJ6C6Ac8nMA0Dygn6iqI8yLg8VxdqKLZGDknL5egcmXCsUa6y8jJHpSlUqFChhEpTWCJ2fupeAMDs624d8ZUsDXv/8C5kNYZOZHnM52sh6cjWDFBNg3MFJgJ0Al3vv0wyCXORsd2jfJk0ZGFNz6kSRRonjBNvWlnZroMeY9SfUehsY6QLQJ4ByTnx7ehxg+RcAlNXQN2A6hrcTnqyLU++Vv6ryQ8elpwHFRyOrElSp11YNqrlWO/YfWQax28eXmJdpSksFbEXfwPA6ARFHhykKtNQmYHKDEgxWJNEJiw4Mz0dnffeN4O990lRmEnEyagcj6MjRm1LSrOpS/6DySQXYLU48ZsHoHKgdlYazdTOhOaQVBD0hA6RlFZiKeT6386cMWCApKXg+2VGqdSkKWpAK9vkh9ans3Hyg4cHmqjUD0sSCrZ/w1NE9NXo2BVE9Dkieszud9jjRETvI6KjtvfDvxjWxa8pNphQaDQ7SFINpRhFOwVrJYLArqaUMFRqgEJJByZDvo7BI3a6Wb+EsQlEnDGUI0btSM2Dp2hfpT/BId/KSFrwFPBuS88rpGdTqeE4n3rhgC15T74CAFBDg63QokKEA2mC6qgQpoRce4mYZT1iDXweS9UUPgnglV3HbgXweWbeB+Dz9jkglO/77HYDpA/Ehsfs9Qcxe/1B7P7M3aO+lEti3x/dBa0VlGLZMgNKDdiIdmA6EuJjQxKZsB757t4OfpI7ktdCqiepkAiEqdnsyBRI5wnZBdkwoOpSETZA7ZwInOwsITsrjMy1Zy07c4dALYXkdAZ6tob0bG/4eGL7vG+Hp3IKzNAZ+4QsR1e/nmshdn7k0IrZlJaDJQkFZv4bAKe7Dv8cgE/Zx58C8PPR8d9hwd8D2N5F+76hkabrP+35BVeewfaJeRhDIhyIQYRgPqRGMh2ZvKbQPQmuu+tIqSpRGJDY1xKojmgJ6TwhaUEqIm2twez1B/td1rKRbzEgA9TOMpI2kHRkc8Ki+aRCdp7QfCKBqTFI92d5+urPvgtcN5KwldqCrZYtH++Q9KZIrFnhvzPWVQepnQ8ewuwb1yYKthqfwnMipuZvAXiOffx8AP8cnfdNe2xT4NF/83a89P/8rVFfxkVRTwpcPTaHq7bOYceWeRTtFLqdwHRkCzyHNivQPY4Q1wT4tm9sNQUtIUKTCB9j0iKkc6HJ7KDgyFmKMRE8DtmcpF3XT7NPuKo/k6B+SqF2RmFPn74d1NCWlh6gAtD1UBhFHfJdsTxN/WIkMyNCd1PdYWIg0QdmZqLl5bAR0Q0Q8wLXXnvtIC5jzZBcqlHqiPH03ARqaQHDBMOE2lgHRisUHZmxnCs70UN24+yvl1f3ElORfQ62WYwFAJbV2tRCyYBJB/+76Ib0bdB1eGGm63INeUrILgC6BiRtoHW1nGD6RFGyZo58LoWB5ZJod2U0kkQ8PKiXO2IUmPywODxXwsq8UqxGU3jSmQV2/5Q9/jiAF0bnvcAeK2Ej95J86GfWr1/hRz5/E67Zcg6ZMsiUwTNPb4XRCoYJKmXZ6hpJzVx0RWRXKBTJemJIvYPtFeFUdipkc2nOg0S+hdHZCuRbxPGYb2XhaCBJosrHgcJu6byYA9n53u/02KvuBCwDla8KtVqDr8gsojZztr6jn9axVtj5kUM4+aabcHKV4d3lYjVC4bMAXmcfvw7An0XHX2ujED8I4OxGbAhzMfz837551JewKE7OXo1Hn7wa51p1zHUyZE0pMdbtBPpCCn0hhckTmIJAtjEMdQmGvffNRIVCKNnZLtXZmQ1QkFLnFEO5gR/9LenlQJFiQ4UVTApIW0DtHJDOAbUzQP000Hh6EUGXWt9Em8QHkooJ4RrXqDb1pDmPUldQndFkDCw1JPn7AP4OwIuI6JtEdD2AewH8JBE9BuAn7HMA+AsAxwEchTSYXb8zaIX4zz/0IVz/hdeP+jL6gjKD9vk6zj26A6e/tQ15O4XRiYQfXc/IxEYicgXqqN4mss7fZoudvDZgCVYca5EICCC90J+DYVBQbUB1ot6QhQiC2jlG/bRsSdvSyrcZZIDvmjrSZyDxIegahx6TOZB0gqPVC4jc9p0ckV9595FpnPjN0TB/LcmnwMyvWeSlH+9zLgN4y2ouaiNgPG2P+hJ68LI3zGDLjgbmn2tndcKgZ2rQYyYUQgFSJJQaGJu8033zkekKhzvOBWs+AEBSAL5tvFp+E9PlwPE8OHakpAMkbfk8dyybY6g88CKcf2Gf9a5moIpEcjIUo2hCqi2ZbbNdlFUDg5Gk9+0+MlgmpeWiymisUKFCCZVQWCEmkvWnKYw/keP5f/4Env9fC2w5AWRPZhI1sDyHoe00wFbf787e23v/TIlwBWTPYSqTsUDCgi7j8Oitw+vU7ZrEuhCpSQFdt8lIhbyedBhJh1E0CZ0JiUp0Y/b1t6BoSi6Drks9h3SoduZCCKt6rcEA+96zts7Gbh/PWqMSCivEe777T3D7l39x1JdRwtijT4PH6qg/20bjWcbWY+KRR66AzIDspjIDsp67fjazm/yOe8CFGl1DVukk7Sbn8hmbl4uv3bcfphYJhcxyx9SAzlZCewehtUNh4SoFMuJ8TNqM77nxCL7nxrJvQY/rwEtpMxldZqbJOBx3/SzXOPq8e2Z64PRqy0VVJbkKNFwrpHWAnxr7VTAzVL2O5LlXo7ajDl1LkbQJZk5BbzO+AIoNiaagqcd2db0YwSFhhgg9NIZUhF4Snh16mIiio044yORlJB0biViQ1/NxQDcoMDbHsELFU9oTi6PRfobjcmT3ndYw5XnXe6dxYondtIaJSlNYBd7+kj8f9SV4mFYL3G5DnzsHygskHQOdwTMuq3Mp6IJspp2A59K+dQKkg5PRrZaqEO+/akvYjgorJQh+Qg4baUsmfboANE4zsnlGNsdI54HsQljOk44cq5+WfTpfHmf2hpuRnSeotpg+LsJAGj5EWaKms9t17x6+CZEs0oRnrVEJhVXgC7M7R30JfcHnziM708LCtxF0M6Jzd+r/vFCnZRfKN+G+e2ZECORRko9TsaNVN2mJgJAPAx555/6hf6evTO9Hdp6RnWeoQqINICBtM0xGqJ9lqEIiEKqQLd8iSU/d0A1G0pJwq6khUN5HZgW6zAddG+7323vvDI4OiV5tuaiEwirw/Ttn8bkT3z7qywAAUJpCjY0hfcHzUXz7tbgwOSEr6xwhXZCOTb6PpKtX6FpFXUERZyh1XSKWVUx1ZKLoppwDHr4/oXyBsulMuj+ZRPbZnAET0NlC6GxRYEVob1fILgDZBeA77ij7FUyNrbOR7XcK+Rduk98gOByH2Vpu3z0zQ3XULheVUFgl9DpoLfST6lVgw4Ax4C1j0I0ET/5LhQs7DVpXG+QTNiUZMq/SeVklv3qovMKb1JZHu67RmWy6FhyNqnBmhAy2lkJB1wi6RkhbjKJOSNuyb29VaG8nJG0gHyMUTSBpsSejzbeWvYXOu590JKpiktAgx73HmQ/SJFfet+u9Q6qaXGetRSpH4yrxyt1fxyce/Vd4w3X/bWTXUPzr7wOnhHwiQWdCobOVJMswIeg6o9iugU4SVH6SDMAYu2emgcxWEZJMHGW9C8o6HE1Nip7IshWpHHjk7cM3HRyMVeG1AVgRCi1RhnxCtB7dANIWo7OFoJtAYQucklbZTDp28xT23D/jtSGVi4+EEWUwkqsQDWXhw8C+u2fw2B3rR0sAKk1hIDivmyP9/OzZFmrPtsEEnH4xcH7SIN9moJuiHdSeSVA/TT7spmviOIyRLEhar7KEyLrOvqZB12zBkA5pwHrAhU9LwVdm9uMrM/vBKaF2QXpVmpSQjxPyLYTONtlcnUQ6JyXdYOA7fqtsQrAVbiqX85324L4zJyGdG0CglB8g1qNAACpNYSCojyg0+bI3WP7E79vqbd/GKZkk7efmoFaCdEGIUNJWSFQyKfC1+7tMhzp8yzjShMSwL2jQDYax3IZkW8KrNkk58whQjMmKni5InkI6z8i3iLaQj8OnLBt7fbrO4K6/yCUsgWyKdlfo0bfPY5Qp2wYItQ5Ks/uh0hQGgDe+6K/x5od+Zc0/t2jKdvq7Dc7uA87tAjrbZDWrPZWi8ZRC/RSh/iwjnWdR/y33QDcce5JJZRWNoTqigjtvvMnEUdePt2AtkCxAtINxQtJmFOOEZAEoGiIsivFoUgNWWyhPwKMHp2DSkLAEoBSCBCTiYOocfo8BsjFd9+6ZNTW9loNKKFSoUKGEynwYED70fb+75p/ZukJWv9oZhWSBwKmozq2rjBCOFKJiu1Wzdrb/OPvumQES2HJi+PRnt0JyChhiXzqtcgIZFq6DESBtSWcn3RCfQtEAVCIp10lkJriQq+4KsTpwKj4Sx83ILpcDNmPS0lj6bK5Ii1gpXBLUqH67paDSFAaEjz3yw2v6eTs/eR8Wrs2xcG2Ozg6D1nMMinFhJao9q1A7Q8jOiwqcT4iqresycb783rLaKiq3xO11Hb5Fu6M7dy4T3bBmQzY8b/xS8I8fnZLEpHFANyWr0tRkrzP5PqYu313XJOcgaRNe9K4uZ2OC0ndx5pGr8eAo4Qvs+CVWd+1xQ971ikooDAh6rX/KjvLJPJxIO/lii0HR5NK/mi4wkgURBioH+vlETQaQrRJ0z3XNCQn2jWcpituvSb3DRZBPSPSgGGMUYyLUijFJrDI1IYVxkQShXAv5Fg6u8MhVYcIWenFifQk2d4FMoJNXBa24avLb7zyCR96xH4+8Y+19CS++tQ/pzCKohMKA8MYX/fWasjFl29rCUNzQwqhELF2fW+RXOVOTEmNTk9qBfkJhz+EZmfS2MxLYlROj7HRrCHuzS3cedSWfSSUzUeVCraba0s8haUuJt+uUzeSSsNiHW0uw5oFJ7XmJ7YZly6aV5Z9UncAErVbArPwdv3UE37hrdI5FtYxK/0ooDBCZWjvurnwh61FtJUogFOjpvGgJ6YKk8poUUheQl1dLZXspUGE5E9JA7R7ztlJOUDpoC6NG3IY9XbA5BlYYqBxi/rg6BhLhwYQeEwIUKiLj5FTSVnNyHaMiv8KKTIjRBGoAAC+56Qi+cmTpAumSjkYi+gSA/xXAU8z8EnvsEID/DUAHwDEAv8bMZ4hoEsDDAB6xb/97Zn7jcr7ARkZu1sbQ3vnx+wGtAEvZnrSVEJLaBCSXNhtH4dJ54J8+0md1t/F5cjc7B2ejp1gja29ria2bAXWAWi1crwmXjpzOy3MyAEfFTNSx5xF6rp1hv5stiColK2n5PZ32AYi/Zbl8lN95+xE8/J7RaAnfedsRfP3w8j57KZrCJ9HbMu5zAF7CzN8N4FEAt0WvHWPml9rtshEIAPDx7/8kXvxn7xj659CCgppXSFp2a0segTAVS+pv0mGwInDqohL9J7LSVLrJpVxaHGouw9EJhG5OhVHDaTQga+5Y2nen5bg6Bk5DenY3N8Kxg1MhpTllvwFW0FyQHIjsvC0fL8SM6M6QXAzfefsRfH1EAgEIqeHLwSU1BWb+G6sBxMf+Mnr69wD+zfI/enOi3VoDD5xt4+bUeOdQM5lzmsnST8Zm6oH6qvz73jMDpDadN8roYwKQhAzIuDgIBDzy9nUUTiPbHMaIw5UMCVNUZPqYFN7P0i9qIhmNVDIfmMpmAqf2+xchOrHesefQDI79h+X/V4PwKbwBwP8dPd9FRP9ERH9NRGsbp1sHOPpvh9tSbueDh2xD2OAUg1ftLVVZCpiMYGxVocmAf3yw9+bwZcFu9XQNUmK6MkdN5uL36yia9vDd+6WikUN3KicQoCJNAsHxCCPcBTE4gThak7BBSXq0i2q47x3zRV4K337n6LSEnQ8ewrGbVya8VyUUiOgOAAWA37OHngBwLTN/L4ApAP+RiLYu8t4biOiLRPTFp59+ejWXse6w82P3D2/wVDo7dd/AJhUBUZrMGoFFqA8856JBSfPwhKh28+Qj68DB2AOyxVrd7ePjlOVuIdf1e5x46wGbkxCawXBiC67qjGJMOlPlW+RxMSH5GhcLTY4q2jD56Xsw+el7MHvDypvRrjijkYheD3FA/rjt9QBmbgNo28cPEdExANcB+GL3+5n5QQAPAsDLXvayDaCMLR3UGqLD0ZCo9p2QBCNed2EgclCOPUj39ydcd9cR2/PAlg07Hka7JLIKHZxdqTT1C+mNGkxBnaeLJBddylFoHa3sTrSqkXBWsjXNKDLRetwTHt9xxxE8fPdoNAQaQCXnijQFInolgIMAfpaZ56PjVxNRYh/vBrAP0i2qQoUKGwSXFAqLtIz7AIAtAD5HRF8ioo/Y018O4MtE9CUA/wnAG5n59JCufd0inRuO4T35O/fCMQ6L2SAbsUQRXITAed5ddl7fpB2HKJQg5wtLk65zUKWV2OqcrQ0f43Lw6J37Jeuyxr7q0dHSlzZ7jBPxueztbhzb3R0qUic4/g1S+SzOAvV9N0aVAr77M3fjxC/fjhO/fPuqxllK9KFfy7iPL3LuHwP441Vd0SbA0Vun8P2vm8EXPjVgL71jD7HwsXPLCaBAcKa1yoPP4B8/2sfJmEYmAyJHHIWQnod1NOohtoZbDUzNRVkQzImLQL5n+STTMFAtFSI6NpLh8x6ilnsw5F+ffL+UUp/890LNvve+GRx919pHZ77rs2/H8Ve/ayBjVRmNQ0LaHvwEcn0bfKFSYbPuCJZxmT3ZqGvWsphz0DdWcVEM21re1IMD0zE1GVv/MMx+kauGk5U2Xdu1l2dlNQRlv4vLRei682dvuLnsa+CQxcgpByckw/fk5DRoawCw64FpHL1lNOHaicbgOpZVQmFI0MNIV8jl73LOMnfTuzJn3yFa23vaZvt1Y+/9MyFmb8/jFOBaSN4R88OaKdYbP8qmp5cC5VKwRLkUL5U2Tb4U2lPdkzRyLY0RCVBX+yFRGPe7UhAW1LUBWNTzOGS8/K9uxt+94r6BjVcJhSHhHz492Am09w/eLQ/YJhXFvgAfky/XLYCBLz/Q6wNwNjKAYCNHKyv8+6NJsI7vlOP7DyC7QEg6Qj2XdKQewmVkJi3J+PRt5jtWWOTlWcwZh4Y3mnxzFt8py2V35vY3KUIIc/L9o2kd//K/uhl/8xOHBjrmOv6rNz5+8DXT+MHXDIa+S2slaquzbf2EpRCPt1yCrCyxyCL/bshvsGXRqTjOkLA8ThmmbsBuqzFMbT0mKURwGYhkSWByePPKZSN64pSUfQ5HjJNvvin8hgkHP4sd39Ss1lS35ekpg1MjW33tf599f3TXwAUCUDEvDRX52GD1SUoNmBQYBgTl2wWoAoAmoIBPUZY3lN/v1GVOI63Cll2jZkAEsKbAWuxzFhi0zoVCMcbeZHIT3hWt+g7SJFmKwrXAfTkhTC3kJ3BTSxepMQMqSASkJunizQDVjFfY0traVcgCwPf+X3fgsVfdPZSxK01hiHjo41N46ONT+MH/fXXawks++3ZJSnGOLofUruzOdEglA083GXqM8Y13lU0Hb2ZYweEFQsZQmUFS00iaBZKxAqqhoRqFbM0CJ19766q+w7Bx9JYp6AkDzhh6zACKUYwZFGMGJmXkW7WwOmf2d2pIKHfyQ4dL45hxDTOuRWuKwpTc1CJ4ayIQkqYGEaM+lqM+luOSIY8BI0uGJ6QrobAGaO1YncZgjEKWaaSZRtLQoJoB17tWJruqG+sk7AdfBZiJygvrP4ARDcEYgimUrIYAKGFQwlDrpFT6UuDxAqZhwA0D3RSzh21OATGBawbQgKnJym/qpscRO3v9Qcxef1BMjEL4JahDQK5k31FAR0F3lO3eDSkmA/A9f37nmnzPH/rcQfzDK+8Z2viV+bAGcASrK0WiZFXIO1L9Q4kB6wTsVicXRQBsQVM5nwEQR5hfAmysHQmDMklCSDL5DJVpdM7U5RxrRiRj6zG/uQ+YQA0NbiWyortoTd2AHH2dPxeeYq0vnO+hQ+AaQy0omGYwI5ArqPFC/hMAjWYHrc7wK2T/l7+8Bf/9FUOsrUGlKawJvnHX/iXX33fjRz5/E8bqHSTKoN7oQCkjhCBAaFLCJGpxJiujydATL+eaCVwBNvEGhsC52BO6k4CZwIagxgok4wUoM6DM4Pir71jV918rPO95p8EMqIkc0OTzOUAAtuYi5LYWUkC2RfZ6W4GdH13EWeciPY7D0UUeNCEZL8AGGBtvY2y8DWMUlBqu3+Xlf3Uz/vsAQ4+LoRIKFSpUKKESCmuEzvaV2eXjWQdjWY6JRhv1rECzkaNWz5E0C/GCZwY8pkUTsNoA+vkAMuMdk/KeAjRWgGoaym56LkU+n8HMZdBzKbJGgayxQUwHAH/3ivtAiqGcU3ZLLpvtVwGb31Hb0QKlDK4ZUM2gcdVCz1izb7wZqBvQ1W2gYYCr20DG4Cs6QGqQpBpJapAlGlmikaYaz912Hj/y+ZuG9v3Gss6lTxoAKp/CGmGl7MdjaQe5TpAQI1GMNJFJ6lR9QNKfyfoXTKHA1EfWKwCOydkQKGExHRSDNSFJDTBeQCUaukjAxcZcL3g+RZEyVLOAOW9t/IYBzmVQ2zsw8yl0Kt89Gc+hF1Lkaf8KJlIMNhCfS2pgUoMkM2huW4DWCldOzKOj5b3P23oOuU6wZ9szQ/lev/jf3oT/8iMfHsrY3aiEwhph56fuxezrlhfWu/l/vgrfVq+jpjTOdJpopjkWCrnRtVFIM4lA6CLc1EQ9Pkbs+r33QNUATuUFlUrrI6MIPJfCUCKEppqgKfUOyMdetTbe9IEiZWRPpygmFLILIth0UyGdIxRFHRjX4KfrwEQBc7oOmiigz9Uw+bv34OSv3FYaitsKnBLSZoF8PkPaLFC0UrQTA60VFuoZWrl1NKYFiHjg5L2v+K9vAwD85Y+ujUAAKvNhzTD7ulux8xPLcxJdkc5hayqqrSIGEaOZ5hivddCs5ajVCtnqOdJMyANVZjD76wdL45h2AtNKwJpkMwSjCaQY1NRQ4zkoM1DjOdRCAppPvBay0TB7/UFAAY0nw+RsPKUAln3tqRSNJxWSMymyMwp0JkN6JgHO90YOrn7BGVBqUJyrgTLZp40CnTN1NJsdXFioY1uzhW3NFs63a9hWa+GJha24+X++amDf52y7gbPtxsDGWwoqTWEN0dzeWtb5E4mcvzVroWCFwjSEJUn3/m1JYiTPQPeuVOlYgeJMDcl2sUn1uZrwPKYGlDBMnoBSiWqYHR3JTRgAg8+oUD9FMCnQfEoEW9KWJjFFE6g/SyjGgOZTCvk40HiSUEwwsm/1/m5f/On3YPIDh5HNKxQdsvs60pbCBTUOFIRv5fI+3U7QzjPRIIrBhCa/40/fiYd/4d6BjLUcVJrCGuIbv/gOTP7u0pJOPv3YD2J7Mo+6yrElbWFL2sZzmucxkbVxRWMOE/U2xusdjNc7MIZQzyTHuTsstvcP7xKn2PYOksQgSQxqO1oYv3IejYkOxre00NzaAhcKRpPsc4VGo09/uQ2C2llG7RyQnWdk54Xqvn6GUX8WqNk9ANSflQa8tWfJN6PtRnZWpkj9lEz++ukETEB6KgUYMM/UYZ6pgxLG3LNNEDEeP71t1d9h8tP34OFfeOeqx1kJKqGwxmiMLc2DnHOC3FbsGCYUrJCbBC2doaUzKGKkyiBVBmONDtLEYHys3cMmrfMERZHAdBLoQjaypojbmvUOtl95AVddeR7br7qA5pY2vv7z7xz0V18zzD+XkLQYuk7QdXlcNAhJm1GME0izr3h09PC63ttv8bumjqAYZyQLQpGv2pKz4NrqqbbyG8+loMxg4XwdSjH2/dFdq/oOPDc6Jb4SCmuM8cbShMIVyQVkpLE9mcdY0sF40kHBChOpkGnM5xnaRYp2kaJTpMiLBI1a7+o+vqWFbVvmMb5tAbW6hDM78zUoYrTma5ifr2NuoY4Lcw2cn28g1wm2jfeG6DYSHnnnfpgaSv0wOAE626XxTb5FzIp8XM7PJ1B6DgAvPngEX5nZjxNvOyC1ExNSWVpMsO/SrXIpljJjRgRDKwFaCVrzNXTmVtCFxWLnRw5JSHREWApH4yeI6Cki+mp07J1E9LjlZ/wSEf1M9NptRHSUiB4hop8a1oVvVDz0M3djz2cuXt12+Os/haeLrThdTOB0MQFlE/THkw46JkEjyTGWBQEwVpdMx6LLn7Dvj+7C/HwdF+Yb0FqhnhWoZwUmts+jWcuxffscrtp+AWONDr7tinNonWpi7nRz8F96BOhsJeTjMtFbVxKKcaBoSOt6XRNBYOoyufWY9HfQzeBHKSbCWKYuKc/5NgNWjHyrkVLqjMEkm9kmGZPJtg6IGI0tK2NC2vnb949UIABLczR+EkLU+jtdx48wc6nEjIi+E8CrAbwYwPMA/BURXcfMa1tXus5x7BJpw2OqjZwTbEvmcFpPoG1SGBBOtce9EyuNaIIUMcbqeU9t/cRYC42swLee3gaTKLQX7HtrGsyEWlrg3HwDWaqhjcLW555Hs5bjf/zU2ju3Bo32FaHLNGkxwUAMbZmXHMeCayaja/J813ulovXE2wNhim4Kf6OvVbcNZ03deAIWbicgTdAAUCi0CoWdn7gPs2+4ZcnXvPOjhzD7GwcvfeKQcUlNgZn/BsBSGZl/DsBnmLnNzCcAHAXwA6u4vk2JS/WbbKgcL6ydQkPlmKw9g2vrp7Cr+TQmJ05hcssptHWK8ayNuVYNc60aLrTqPnkpRjMrMJF1cO1zT2PfNU9h8ppTmLzmFF58zRN44fYz2LX9NF6444xMGEjh1eS2zUG+fezmqRIdG2B7V2iC0raJLmyHaradt7U0k03a5XDsybfcBGJpYEsFIbsghVTZ2cT7FNIzCVSLkJ7OoBYUklPZsvt/ZGdHRAPdhdV4M24kotdCGr0cYOZnATwf0lvS4Zv2WIUI/SYwALzuH94AAPi2+vPwNX4+rsou+LDkM/gG/IsAABnvSURBVPkWZKSRpRq7tp7Cgs7wnG3nAQCpMsj7hCLPzDfRrqWYqLdxemEMW+qi0ipiXNM8BwPC85pnsWfrM7gim8O5ogG1XrrHDgAxU7VnXmLpPC0dpRi+R6ZlrlqM6Fbl8n5VwLe7FyETGuaw5chUuXVI5kvP9bjuriM4euf66NG5UkfjhwHsAfBSSKu4ZbOIbOa2cRUqbGSsSCgw85PMrJnZAPgYgonwOIAXRqe+wB7rN8aDzPwyZn7Z1VdfvZLL2LD46s++Sxq7dKGZ5GgmOcZUBxNJG9uSecybGr584QVIYPD4wnac7ozj2fYY5osammmOZpqjnhQ9/oSf/9s3Y++Vz+AlVz2B54+fxe5tp0K0wqT45tx2zBU1zBV1PNWawMn5KzFX1PG+7/39tfoZhg6TSBOYbsp3AL7dvONpjLUJVn2a0KqI8NZSu8WU976ztevdSUL0erF+kw7X3XUEj965fprsrMh8IKJrmPkJ+/QXALjIxGchTWVnII7GfQD+YdVXuQnBfbT0by1sAQAoMHJWaJsUO7I5bM8WkCmNq+oXcL5o4HljZ/FMexxHz14FAHjulvM9Y53PG9hRn0czyZGSwdW187imcVbOr59F22S4Kj2Ps3oME0kLH/7Gy/H9z/v/hveFR4DH7hB1fO99M1IP4rhnHEW73RvYvUKwObo0/6O3TGHXA1YhdqfE/6E7pgmU9B6/GHidMVtdUijYtnE/CuAqIvomgHcA+FEieinkK58E8BsAwMxfI6I/BPB1SDfqt1SRh/6Yfd2tPfHoh598LgDgm2PbUWglefW1Fs7ndTTTHFuzFq6ozeNcUceO2jyu3XYGADCR9Ya/rm5cwCOnr8bDxXOwtdnCjsZWzOUSO7+6uQNX1ecwr2t4or0NzSTH5BWnsSVdXhr2hoKbdwaBpSrmYIyYpvzzbthiM9+oy/ki7GvEdoKbwLBNl3Ar7LtnBo/dvj58CQ4DbRtnz78bwHBoZjcxvuuzb0dmU+bHshxForCt1sJXH78GP7BzFv8wuxONRo5OJ0GjkWOslqORSsxNdXnHfunvfgNX1Bbw4qu+hfmihm9rXMC5vIEXbXkSAHAmH8Pnj1+H73vBP+Pvj+6SMuqzNeTfvj6834OGinK6XGs8dDXKIQAczeC+1ecdKrXa6wv7V5DTRoyd+Lf1Tvx971l/AgGoCqJGilhLOHdqHMqSsV4420TWKDDfyVCv5zhx7gqMj7WxY2wBrSLF9sYCznfqqFtuhf/8Qx8qjfulx5+PZj1Hq5NhotnGhbyOC506zjQkMWlr1sI1O87hVGsc27bP49z5JtSONj73YyujjFvvoIJsPwzXH5K93Q+E1b+kORhgz/0zOHYwTNpjN02FxrSMHhOj7zH077+xHjUEh0oojBA7/4/7MPtrIbmFz4p6z02N/Okmnk0aUG2F+do4UDdYaGXQRYK58Rq2NVt46sJE/3GvfBZn2w0URuHU8R0wu4BnT+7A47Z3g1pILKejZWNqKdDY5rXyHnnnfuy7e8YyV0fLvG0jRxo+HOkmsGgOfQYz5XN9Q9rIrCC241hTpV+Y0yU9rUdUQmGEmP21W7DzI4eAjEEZgxsyMVWmYcYZKjUw9QToKGRPZ8hzSZKZa9ax0NkGfm6vD2DPZ+5GVtuO9kKGejNHclUbhU6QXr2Ael00i9ZCDVmtQH58C+jaOfDT49DjG4d2bSXwXaISl6tgJ76d2KS7VvRF5iyxaBHcLUSMFQjuNR32IGDf3TN47I4pH414bJ3kJPRDJRRGDNIkPQk7KnQzbiVAwjBa+g0gYRRbbIOTbRqoG+iCMPvLt/eOd7IJbhHSOqPTqAOGcL5eB9cYhUvJzQyKWgJsL4C5GrBNY/ZXb+sZa1MhChcaS4lvEmnK6xpKg7sSnlia8R6NTAiVE3SDfcc+F9T3WkX83Dk07fjr1YfQjapKcsQ4+ZabAALS88qn4abnFdJzCbKnMmRnE6TPplDzCtmpFMmFBHQ+RXKuv1NQj0klXzFuORvHTLhjrUe8/mQKupCi9mSK7KlsXauyg8LRW6dgEhEIrts2gChqUFbzSZf3Do+8XfIJ3LmuyzdgxwFC6DMyH5jg063XOypNYcTYPTMNRdIqXbVslyfb0o1su3gqxDnGTKidI+RbyokzDnvvnUGWKx8WE7WYYGoMdT7xCTu6If0LdFMcb5eDUIihivC7+pUdEGeknREqR8hl6Ic4NOlOVWW/gu++Zc2Ifv/ZekSlKawHWD5EyqU9Ohn4Yh7VkTtMdUjKdm1d/4m39rY9zy4Q8i0G6RwhmyOkC4RkgZDOEZK2tGNPWgQqJLzW35O2eUEMcbDartLeYYiyL4C0ZCgyyb47u1F1otBml5ng8x+wcX/eSihUqFChhEoojBjCDiSrv6nLxon1eFn1lTSBGFBF5Bvog/YOeaF9pUH7CoP2DoPOdoNiXIhBdFOIRIoJ4wlFdJ1x4jd7tY7Nhr33zkjvDQ7t5k3G3lTjeG8Tm3xdRJeR/ehvTQlXAwfNgtDlh6Dy3kciNgAqn8IIMfn+abhGrqzIp9l6R5ixtmm3w6pP3HvP4Rl7XMYhHW5qB+dTkDJhEUAbVsddBvYcmsGxW8Xrb2riRzF16XPBDQPVlufORAMAck4DosV/oug4w6Y0u2M2nwFxPsMGWYI3yGVucjjPlG36KsYshckfJcmognB8qndld+ExMvBjJG0SgtEWIWkpJHN2W1D+mNrc6QkAyvkHnNpGvKkkb3HKMA15rhsm8DrWxPdgUtHads/0ZwfgyDVTqotQwc/gMiXZ5ivsu/vSlZOjRCUURonE9n206beyMnFQSTW8U9A5HheDKizxB8tjp1XAhBRfVxbMSu5cVozj+zev6bB7Zhq7Z6Zx/EDIDZh9482hKjERE82Zb75zdxYEBwh905R9LUOkHbjyaheS9FmRHCITvlP4OkZlPowIOx88JL8+Q/LxI0cBp9FdBfiMGnKNUruw756ZcANG8XNv18Kpw248sjfu5jUddr13Gif6aFQAgmrP4fekqLIRgP9fHDMTLdIxyyc7AT5dWl6INAUTRSXsMIsVSa0HrHOZtYnhym4ZwghsVy1fwZdwWKF8lh3j2M29N5JxNOZptCXwmgEAb1qIeWG1kEWoxzY6dj0wjRNvW1wDckliVJDkaWiS/yP6T7xAcOcahGIoh/h8+/cFclf7WS7kGVVNOj/DesU6vrTND7f6kCFQHv4Kshx/PlvO+hgWAydcsm17btRIhXU3IyvJ8tuUuESOkDfDXHJSv/NZUpqJgyBFlxA9eutU+N2jtGdOXBTD5UQE34M34dZxlXolFEaA3UemkcwloDYhWVB2xQoJS3EYEoD3NXS7wXdPz2D39AzA5E9xEQv/WCPc+NEE2ET8rCVMfvjwRbUEADjx1gPgRRiWYula+rkXkckuhOnqKVhFforIUemTplL2UaDd0+vT4Vj5FEaAdE5uPB8HT7puQNubwN9kAMBUcpgBKM1sBgUVNZrwpUKdKJqBDRIzXyp2/vb9gCbMvmlpjVQcrwIYQGK1NhLHLoCy9uB+U9XLseDDyJGDEegyD5QLJbP38XiGpnWISiiMAOJD5KhQBqV/wt6fsspYUD9Sx9I9xfbGpGDPkpctso9u1PXq5FoxClpeZyXHi1CQCIVc6k/IN5Bxf4I9f7H5GykcMSsTWSp4T+HWz3+zTtW1ynxYY+w5NCPqpu1vyM5BqBBV8bEIBBe+uoTq6n0FBFFVE1FRjY3J+70bf30uUCvG5AcOL7vV2skbb4LqyBJOtj+D1IW4BjLWMYsey8tj98w0jk8d8Hkj4rCk0HQmt3UmLvvRwJsnEklan3/ESntJ/kHUR/IkEX3JHp8kooXotY8M8+IrVKgweCxFU/gkgFfGB5j53zLzS5n5pQD+GMCfRC8fc68x8xsHd6mbA7ppbENTqUkoxgx0g6VZaeSEIgNfNaly6kky2vXeae8RD6FGsqG0eLNvWJ+a6qox+cHDOHnjTSt6L9nogjfhKPotu5KQgLB3oclSMlmXHydEgrpyS7wXWB6vR2fjqnpJEhEB+CUAm6eDyBAx+YHDUG35yd0+sY1LqRQjt+aAbWLSr5DGqacql/LqpC39EVUHUNrFxcuSwN3w/XIdNiImP3xYSGpWClsjonJJH6ciEgqRM6bbf8uw9RSRw/H41IFgckRjOE4LVUQp7HFe9DrEan0KPwzgSWZ+LDq2i4j+iYj+moh+eLE3Xo5t45KWkpuwJTUJScv2HuyEyV16bCd9P5+CKsLmwo7khIq3YamcwLTJQMvo1dgPx/cfkN+GKeQa2OQvl5Ho8hS8wLC/82KC1SeFcTjXjaGi9HXvY4AImPWE1d4ur0FZS3gCwLXM/L0ApiDdorb2e+Pl2DbOU3i5RCLYdmPWyegci3ESkk+ciXDdu2d8t+QQuoQPm7nP8PkOZvMJiF0PTA+k5Fu1Q8iglFAURxK6SqKXaopd9LQoX2S9BSFWfIsQUQrgFwH8gTtmW9Cfso8fAnAMwHWrvcjNApOxFEPWbDgyZdvF2O6j7Dgf2y56Mw9NTaIXfnOVfdGxOBoByGccPzDVm+uwAbF7Zrov89RK4OsanEaQ262wmw4CNm41183GBADHDk55ZmivVWiEbMjItCCgf0hjHWA1eQo/AeAbzPxNd4CIrgZwmpk1Ee2G9JI8vspr3BTYe+8MlJJVW3Ws2cD2ud0ncd68ivZdUB2USDv86u9s4NTGyVOxlTeLduCccscPDK6y8+itU9g9PQMiKwx8nkH43TzfjXJ54xcBwWaostfeFPdqctAAknUpE5YUkvx9AH8H4EVE9E0iut6+9Gr0OhhfDuDLNkT5nwC8kZn7OikvN+im3CS6IXnxusngFCjGhewk38LQDbaRCEDXRCPozpHfc3jGawcxR6DzTcgeYe+cj50RfOlBQ3Gp3+OgkLjfK7cFUoa87a+KyEfjqlStz+C6uxbpqEXsMxyBKI9ERUEhx7dgHZn9NI9RYaW9JMHMr+9z7I8hIcoKEXZ+9BAUFIoJjWReQY8ZqAUFPW5AbYIeN1AteQ4Aal7BNOWcE287gF3vC/ZzsUVLrwLFpcIeKsQIplz2yjrhnINsvXq6l4pd75vGiSFxP1BBIKsOxJEeH4Wwj127+Yv5FR67bQov+g9HJJvU+iWMiyCpoImUelKuM7/CJlEs1zdUW5aFEI60nIstW8hkX6e2ksf2PS5nwdRMaSzVJtl3qHcrrMlg/RHEctM/euf+tf/iA8Lk+wfjVFwMj965X/wyERENIt9OD9GKjewsNpFdTYX3RcCOEcvlKE3SOZOve/f60Baq2oc1ACuW/HpNMJmsRmzJQ4VQxZoJri9hDYCOmJbsDbnrgemghjob1cHxMUAEgtIAZwDy8FkbEbsemMbJATkVL4ru39Q7fZ2jFn4vTV94UX+ASQEFywVp09X9+51y18W32acIdmSoNIU1ANdk4puGEXWyafxz2CiE23PKIhAMfAnw7A03Y+dv3y83li3J5cyE2oc6Q48ZmJrsOWOfJWnqEo34/9s7mxDJriqO//+vuiODCCqBQVTSPdOtEDdDkOBCJG40yWZ0I3FjEEmCJoJ0zCQRwYBgppPuCplMMqAyJC40ZBPMIvhBNq7ERAiaCHG6Z3owQ8xEBBd+TE/VOy7uPfee+7pq+qM+blVxf1C8qtdV3ff2fXXePd/TSrU9nm+KALGi85yg9vkjSe0D7vzyfuKHT+ywLeyoU2HVBBvYNKGyugiFQqGQUNSHEbJweg0AwEpz9b2BsEvXFq6jxkCfOafGQTVm9aLr3hAKvQLO/03G/PxQp9G9ntaw5uVH29gcU4p31TWGRMCpe96VaHMhbGv5qk/NTCDGm7D2a21rZyKqDsHgKETl7Qp//X7e9So7hXGg8Qb021Of0wC4c67isqRby0a+A//b8pWf4ar4tARynX/4asRaGTpUFyZikZYpY9yFTc89vBLjCNRuY9LSgxuxFQ2RQvjSazv/xy6YzCe69SjHFm0WzQ/mNywUoTAiFk+tJ2XZwy7ANzVll5B5F9omh7ou1PlQjfpQDWn1Kb2uXYt1JxEC65E8VC92VvD8F9l+WVrNU+m4qeOHDEnrPtRIxRrRwCDc0cth48GVJEw6fEb/Vt04Svo6J0UojIjQKNZEMHLbB8ZcVXWicled/7JrcQ70KOqp7kZuE9V25X5/p3IP9VR0fIPaUCikRwm3KSCXHGMzYanxRbVxBe7IIJh7GQ1De3sNeIIxNAJJ4d7wewl88pE+QVFjogiFUWLv3roNnYuVkVy1X++SNNv8rW+m6cALp9ecWlCbeIT/VeAVxsdVhiYwujuRuelTHZaaNRDHxPKP2jj3PfN3TYxB2PY317Mlrrz+XG8PT1A3WthRdj9Ue265snu1Vn6uJPu3sgiFEbD45HpSdj0Ew6i+H3IVvA3A2wL66qdeN63VfuAFSKin0GEoJaYuvKqje9/pYWm1jY0MAmHpZBQIocGsCoCGcTE5SnrnX1pNVYjN767ENdC8FBuzoLYGnyGbVIDOSBEKI0ADjNKWYoKkOrMVEFZo9DIMEk6lqCQaumAuML1wddvbdX9nmrpJL622sfFgHlUnyS/xOwStmWmDjqxdAUDSVaqfLSDcEBoeJbuGYNxF1H5H0RQw46S4JEdAiG+3d32NZPN5C6Fks/lZL8X0hp8+BoAQClgRMu9cmcLo5hJvl6BPstGW6tNErkzOpdU2No0wUsF09PF2/KLr+ni7ouY1QMz/2dbBMCQeBpszEdQQF6ymrk9pCSSzcbjsFIbMwlO+O7FEwyG1FFeIZCMo8S4DAKDg4l0ncPGuE+kvlBhvIIzuzNiFyOinU7qaRx9vZ4ml2HV3EmIIeqgNvllPMEx6NaLZWu78/SuxtkJtzEzBiMlw89CGtqPIBN0PZacwbCiuMUtyLnqv3N1GnFCwb+p3d7ANQ+ydxnykGezELnF+ZfK9DlqGLItAeGx3dUXbwMEHLyX/Z7+g1AXRupq9vBAVdqgXwYHhbU/qWo65ERJKyI+bIhSGDG0sgblzW++C9o1k6BAluHjPzr4FC8+sBeFBLRoYDFwxmk4rOcPfaHr1jZk0Fp9cx4UH8tk86l3Uq80HXPEVIZxaZgVyiHA0gWJaMKWHbK/nxe8ajUdI/A6hMmpmhdjOriakyqNGTOmGs1AojIoiFIbI0bV2LLluahzwqrYzj/tDCkJ6dNI/wGJj7oGk/6PVNmyKL6TnzWrikPl825kj7fUDBXWFWIVeRkW1F4jrN2m58J37nbZhdidqDA4h6+pqDqnx+dIoi/owRELTUHUPqh7pI9tcCTWvOwLueK11V3cWEF1aqjJY45dPtVZ3ZBKEM4EsnFnD1rcG6NcwAPvR00ODGEEonYaq4V0065F4FhpoIlzqyoCzP6ntQr0R5ppQw/XWt8enahWhMESkgjM81UxcURRjLzRRcdeq2umiGM177AWnNQQ7GqikMQqc6ASohadd1uhADVwG4Mh6e19FXzdPrGDppHNNUmMJdPema9MQBH29iYxCBlCvAyDduIOQOS84KpjQ9/3McDgU9WFILJxeC27CkPGoRT+BWPq7S7fgqjbIHr4kDd+2ngs9A7RMOTCxK7pw2nVzyiUQFk8dTGWwoeO2dHvwNihhHdw6Lz/acE1q4xkTJh0iIvWouS9dWzjWRaweaa8ffPL7pOwUhoV3Xbk8efdl1+KpnXnvvqpdCS+aXULV7XdrQdoGnfGc1mGsrsSdgviU6omsGQ70TPIaFwtPrWNrkOhO3YHVcPOwvSZ1XkZAA+ZoqQB04nPC7y47DO0BpYVY5LVjPBP1Na6TIUOZAP8VyfcA/BvAP3KPZQRcj9mcFzC7c5vVed0gIru2Y5sIoQAAJF8TkU/nHsewmdV5AbM7t1md116ZUA20UCjkogiFQqGQMElC4ce5BzAiZnVewOzObVbntScmxqZQKBQmg0naKRQKhQkgu1AgeSvJt0hukHwo93gGheQWyT+TfJ3ka/7ch0n+luQ5f/xQ7nHuBsmzJC+TfMOc6zkPOk75NfwTyZvyjXx3+sztEZKX/Lq9TvJ287OH/dzeIvnFPKMeH1mFAskWgKcB3AbgRgBfJXljzjENic+LyDHj1noIwCsisgzgFf960nkWwK2Nc/3mcRuAZf+4G8CZMY3xoDyLnXMDgCf8uh0TkZcBwF+PdwD4lP/MM/66nVly7xRuBrAhIudFZBvA8wCOZx7TKDgO4Dn//DkAX8o4lj0hIr8D8M/G6X7zOA7gZ+L4PYAPkvzIeEa6f/rMrR/HATwvIldE5AKADbjrdmbJLRQ+CuBv5vXb/tw0IwB+Q/KPJO/25w6LyDv++d8BHM4ztIHpN49ZWcf7vPpz1qh4szK3PZNbKMwinxWRm+C21PeS/Jz9oTh3z9S7fGZlHoYzAI4COAbgHQDjy0CaMHILhUsAPm5ef8yfm1pE5JI/XgbwItxW813dTvvj5XwjHIh+85j6dRSRd0WkKyI1gJ8gqghTP7f9klsovApgmeQiyevgDDovZR7TgSH5fpIf0OcAvgDgDbg53enfdieAX+YZ4cD0m8dLAL7mvRCfAfAvo2ZMBQ0byJfh1g1wc7uD5PtILsIZU/8w7vGNk6yp0yLSIXkfgF/DJaWeFZE3c45pQA4DeJEk4P63PxeRX5F8FcALJL8B4CKAr2Qc454g+QsAtwC4nuTbAH4A4CR6z+NlALfDGeH+A+DrYx/wPugzt1tIHoNTibYA3AMAIvImyRcA/AUu8fleEclQ+mR8lIjGQqGQkFt9KBQKE0YRCoVCIaEIhUKhkFCEQqFQSChCoVAoJBShUCgUEopQKBQKCUUoFAqFhP8DzNtImrKzebQAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "../DINAE/mods/import_Datasets.py:136: RuntimeWarning: invalid value encountered in less\n",
      "  ss              = np.sum( np.sum( np.sum( x_train < -100 , axis = -1) , axis = -1 ) , axis = -1)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "....... # of training patches: 275/275\n",
      "2) .... Load SST dataset (test data): data.nc\n",
      ".... # loaded samples: 80 \n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "../DINAE/mods/import_Datasets.py:208: RuntimeWarning: invalid value encountered in less\n",
      "  ss            = np.sum( np.sum( np.sum( x_test < -100 , axis = -1) , axis = -1 ) , axis = -1)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "....... # of test patches: 80 /80\n",
      "... mean Tr = 0.001206\n",
      "... mean Tt = 0.001072\n",
      ".... Training set shape 275x200x200\n",
      ".... Test set shape     80x200x200\n",
      "....... Generic model filename: modelNATL60_SSH_275_200_200\n"
     ]
    }
   ],
   "source": [
    "# push all global parameters in a list\n",
    "def createGlobParams(params):\n",
    "    return dict(((k, eval(k)) for k in params))\n",
    "\n",
    "list_globParams=['domain','fileMod','fileObs','fileOI',\\\n",
    "'include_covariates','N_cov','lfile_cov','lid_cov','lname_cov',\\\n",
    "'flagTrOuputWOMissingData','flagTrWMissingData',\\\n",
    "'flagloadOIData','size_tw','Wsquare',\\\n",
    "'Nsquare','DimAE','flagAEType',\\\n",
    "'sigNoise','stdMask','dropout','wl2',\\\n",
    "'start_eval_index','end_eval_index',\\\n",
    "'start_train_index','end_train_index',\\\n",
    "'batch_size','NbEpoc','Niter',\\\n",
    "'dirSAVE','suf1','suf2','suf3','suf4']\n",
    "globParams = createGlobParams(list_globParams)   \n",
    "\n",
    "## 1) *** Read the data ***\n",
    "genFilename, x_train, y_train, mask_train, gt_train, meanTr, stdTr,\\\n",
    "x_test, y_test, mask_test, gt_test, lday_test, x_train_OI, x_test_OI = import_Data(globParams,type_obs)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 4.2 Define the NN architecture"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(11, 11, 22, 40)\n",
      "(11, 11, 22, 40)\n",
      "__________________________________________________________________________________________________\n",
      "Layer (type)                    Output Shape         Param #     Connected to                     \n",
      "==================================================================================================\n",
      "input_1 (InputLayer)            (None, 200, 200, 22) 0                                            \n",
      "__________________________________________________________________________________________________\n",
      "lambda_1 (Lambda)               (None, 200, 200, 22) 0           input_1[0][0]                    \n",
      "__________________________________________________________________________________________________\n",
      "average_pooling2d_1 (AveragePoo (None, 50, 50, 22)   0           lambda_1[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_1 (Conv2D)               (None, 50, 50, 40)   106480      average_pooling2d_1[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_2 (Conv2D)               (None, 50, 50, 40)   1600        conv2d_1[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_3 (Conv2D)               (None, 50, 50, 200)  8000        conv2d_2[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_5 (Conv2D)               (None, 50, 50, 40)   8000        conv2d_3[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_6 (Conv2D)               (None, 50, 50, 40)   8000        conv2d_3[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "multiply_1 (Multiply)           (None, 50, 50, 40)   0           conv2d_5[0][0]                   \n",
      "                                                                 conv2d_6[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_4 (Conv2D)               (None, 50, 50, 40)   8000        conv2d_3[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "add_1 (Add)                     (None, 50, 50, 40)   0           multiply_1[0][0]                 \n",
      "                                                                 conv2d_4[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "activation_1 (Activation)       (None, 50, 50, 40)   0           add_1[0][0]                      \n",
      "__________________________________________________________________________________________________\n",
      "add_2 (Add)                     (None, 50, 50, 40)   0           conv2d_2[0][0]                   \n",
      "                                                                 activation_1[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_7 (Conv2D)               (None, 50, 50, 200)  8000        add_2[0][0]                      \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_9 (Conv2D)               (None, 50, 50, 40)   8000        conv2d_7[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_10 (Conv2D)              (None, 50, 50, 40)   8000        conv2d_7[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "multiply_2 (Multiply)           (None, 50, 50, 40)   0           conv2d_9[0][0]                   \n",
      "                                                                 conv2d_10[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_8 (Conv2D)               (None, 50, 50, 40)   8000        conv2d_7[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "add_3 (Add)                     (None, 50, 50, 40)   0           multiply_2[0][0]                 \n",
      "                                                                 conv2d_8[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "activation_2 (Activation)       (None, 50, 50, 40)   0           add_3[0][0]                      \n",
      "__________________________________________________________________________________________________\n",
      "add_4 (Add)                     (None, 50, 50, 40)   0           add_2[0][0]                      \n",
      "                                                                 activation_2[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_11 (Conv2D)              (None, 50, 50, 200)  8000        add_4[0][0]                      \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_13 (Conv2D)              (None, 50, 50, 40)   8000        conv2d_11[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_14 (Conv2D)              (None, 50, 50, 40)   8000        conv2d_11[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "multiply_3 (Multiply)           (None, 50, 50, 40)   0           conv2d_13[0][0]                  \n",
      "                                                                 conv2d_14[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_12 (Conv2D)              (None, 50, 50, 40)   8000        conv2d_11[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "add_5 (Add)                     (None, 50, 50, 40)   0           multiply_3[0][0]                 \n",
      "                                                                 conv2d_12[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_3 (Activation)       (None, 50, 50, 40)   0           add_5[0][0]                      \n",
      "__________________________________________________________________________________________________\n",
      "add_6 (Add)                     (None, 50, 50, 40)   0           add_4[0][0]                      \n",
      "                                                                 activation_3[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_15 (Conv2D)              (None, 50, 50, 200)  8000        add_6[0][0]                      \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_17 (Conv2D)              (None, 50, 50, 40)   8000        conv2d_15[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_18 (Conv2D)              (None, 50, 50, 40)   8000        conv2d_15[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "multiply_4 (Multiply)           (None, 50, 50, 40)   0           conv2d_17[0][0]                  \n",
      "                                                                 conv2d_18[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_16 (Conv2D)              (None, 50, 50, 40)   8000        conv2d_15[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "add_7 (Add)                     (None, 50, 50, 40)   0           multiply_4[0][0]                 \n",
      "                                                                 conv2d_16[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_4 (Activation)       (None, 50, 50, 40)   0           add_7[0][0]                      \n",
      "__________________________________________________________________________________________________\n",
      "add_8 (Add)                     (None, 50, 50, 40)   0           add_6[0][0]                      \n",
      "                                                                 activation_4[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_19 (Conv2D)              (None, 50, 50, 200)  8000        add_8[0][0]                      \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_21 (Conv2D)              (None, 50, 50, 40)   8000        conv2d_19[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_22 (Conv2D)              (None, 50, 50, 40)   8000        conv2d_19[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "multiply_5 (Multiply)           (None, 50, 50, 40)   0           conv2d_21[0][0]                  \n",
      "                                                                 conv2d_22[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_20 (Conv2D)              (None, 50, 50, 40)   8000        conv2d_19[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "add_9 (Add)                     (None, 50, 50, 40)   0           multiply_5[0][0]                 \n",
      "                                                                 conv2d_20[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_5 (Activation)       (None, 50, 50, 40)   0           add_9[0][0]                      \n",
      "__________________________________________________________________________________________________\n",
      "add_10 (Add)                    (None, 50, 50, 40)   0           add_8[0][0]                      \n",
      "                                                                 activation_5[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_23 (Conv2D)              (None, 50, 50, 200)  8000        add_10[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_25 (Conv2D)              (None, 50, 50, 40)   8000        conv2d_23[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_26 (Conv2D)              (None, 50, 50, 40)   8000        conv2d_23[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "multiply_6 (Multiply)           (None, 50, 50, 40)   0           conv2d_25[0][0]                  \n",
      "                                                                 conv2d_26[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_24 (Conv2D)              (None, 50, 50, 40)   8000        conv2d_23[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "add_11 (Add)                    (None, 50, 50, 40)   0           multiply_6[0][0]                 \n",
      "                                                                 conv2d_24[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_6 (Activation)       (None, 50, 50, 40)   0           add_11[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "add_12 (Add)                    (None, 50, 50, 40)   0           add_10[0][0]                     \n",
      "                                                                 activation_6[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_27 (Conv2D)              (None, 50, 50, 200)  8000        add_12[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_29 (Conv2D)              (None, 50, 50, 40)   8000        conv2d_27[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_30 (Conv2D)              (None, 50, 50, 40)   8000        conv2d_27[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "multiply_7 (Multiply)           (None, 50, 50, 40)   0           conv2d_29[0][0]                  \n",
      "                                                                 conv2d_30[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_28 (Conv2D)              (None, 50, 50, 40)   8000        conv2d_27[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "add_13 (Add)                    (None, 50, 50, 40)   0           multiply_7[0][0]                 \n",
      "                                                                 conv2d_28[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_7 (Activation)       (None, 50, 50, 40)   0           add_13[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "add_14 (Add)                    (None, 50, 50, 40)   0           add_12[0][0]                     \n",
      "                                                                 activation_7[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_31 (Conv2D)              (None, 50, 50, 200)  8000        add_14[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_33 (Conv2D)              (None, 50, 50, 40)   8000        conv2d_31[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_34 (Conv2D)              (None, 50, 50, 40)   8000        conv2d_31[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "multiply_8 (Multiply)           (None, 50, 50, 40)   0           conv2d_33[0][0]                  \n",
      "                                                                 conv2d_34[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_32 (Conv2D)              (None, 50, 50, 40)   8000        conv2d_31[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "add_15 (Add)                    (None, 50, 50, 40)   0           multiply_8[0][0]                 \n",
      "                                                                 conv2d_32[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_8 (Activation)       (None, 50, 50, 40)   0           add_15[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "add_16 (Add)                    (None, 50, 50, 40)   0           add_14[0][0]                     \n",
      "                                                                 activation_8[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_35 (Conv2D)              (None, 50, 50, 200)  8000        add_16[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_37 (Conv2D)              (None, 50, 50, 40)   8000        conv2d_35[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_38 (Conv2D)              (None, 50, 50, 40)   8000        conv2d_35[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "multiply_9 (Multiply)           (None, 50, 50, 40)   0           conv2d_37[0][0]                  \n",
      "                                                                 conv2d_38[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_36 (Conv2D)              (None, 50, 50, 40)   8000        conv2d_35[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "add_17 (Add)                    (None, 50, 50, 40)   0           multiply_9[0][0]                 \n",
      "                                                                 conv2d_36[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_9 (Activation)       (None, 50, 50, 40)   0           add_17[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "add_18 (Add)                    (None, 50, 50, 40)   0           add_16[0][0]                     \n",
      "                                                                 activation_9[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_39 (Conv2D)              (None, 50, 50, 200)  8000        add_18[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_41 (Conv2D)              (None, 50, 50, 40)   8000        conv2d_39[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_42 (Conv2D)              (None, 50, 50, 40)   8000        conv2d_39[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "multiply_10 (Multiply)          (None, 50, 50, 40)   0           conv2d_41[0][0]                  \n",
      "                                                                 conv2d_42[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_40 (Conv2D)              (None, 50, 50, 40)   8000        conv2d_39[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "add_19 (Add)                    (None, 50, 50, 40)   0           multiply_10[0][0]                \n",
      "                                                                 conv2d_40[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_10 (Activation)      (None, 50, 50, 40)   0           add_19[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "add_20 (Add)                    (None, 50, 50, 40)   0           add_18[0][0]                     \n",
      "                                                                 activation_10[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_43 (Conv2D)              (None, 50, 50, 11)   440         add_20[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_transpose_1 (Conv2DTrans (None, 200, 200, 11) 1936        conv2d_43[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_44 (Conv2D)              (None, 200, 200, 80) 7920        conv2d_transpose_1[0][0]         \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_45 (Conv2D)              (None, 200, 200, 11) 7920        conv2d_44[0][0]                  \n",
      "==================================================================================================\n",
      "Total params: 446,296\n",
      "Trainable params: 446,296\n",
      "Non-trainable params: 0\n",
      "__________________________________________________________________________________________________\n",
      "_________________________________________________________________\n",
      "Layer (type)                 Output Shape              Param #   \n",
      "=================================================================\n",
      "input_3 (InputLayer)         (None, 200, 200, 22)      0         \n",
      "_________________________________________________________________\n",
      "lambda_2 (Lambda)            (None, 200, 200, 22)      0         \n",
      "=================================================================\n",
      "Total params: 0\n",
      "Trainable params: 0\n",
      "Non-trainable params: 0\n",
      "_________________________________________________________________\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "__________________________________________________________________________________________________\n",
      "Layer (type)                    Output Shape         Param #     Connected to                     \n",
      "==================================================================================================\n",
      "input_4 (InputLayer)            (None, 200, 200, 22) 0                                            \n",
      "__________________________________________________________________________________________________\n",
      "input_5 (InputLayer)            (None, 200, 200, 22) 0                                            \n",
      "__________________________________________________________________________________________________\n",
      "model_1 (Model)                 (None, 200, 200, 11) 446296      input_4[0][0]                    \n",
      "                                                                 input_5[0][0]                    \n",
      "__________________________________________________________________________________________________\n",
      "model_2 (Model)                 multiple             0           model_1[1][0]                    \n",
      "==================================================================================================\n",
      "Total params: 446,296\n",
      "Trainable params: 446,296\n",
      "Non-trainable params: 0\n",
      "__________________________________________________________________________________________________\n"
     ]
    }
   ],
   "source": [
    "genFilename, encoder, decoder, model_AE, DIMCAE = define_Models(globParams,genFilename,x_train,mask_train)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 4.3 Train DINAE with Fixed-Point solver    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "..... Start learning AE model 2 FP\n",
      "..... Update/initialize number of projections in DINCOnvAE model # 0\n",
      "__________________________________________________________________________________________________\n",
      "Layer (type)                    Output Shape         Param #     Connected to                     \n",
      "==================================================================================================\n",
      "input_6 (InputLayer)            (None, 200, 200, 22) 0                                            \n",
      "__________________________________________________________________________________________________\n",
      "lambda_3 (Lambda)               (None, 200, 200, 22) 0           input_6[0][0]                    \n",
      "__________________________________________________________________________________________________\n",
      "input_7 (InputLayer)            (None, 200, 200, 22) 0                                            \n",
      "__________________________________________________________________________________________________\n",
      "model_3 (Model)                 (None, 200, 200, 11) 446296      lambda_3[0][0]                   \n",
      "                                                                 input_7[0][0]                    \n",
      "==================================================================================================\n",
      "Total params: 446,296\n",
      "Trainable params: 446,296\n",
      "Non-trainable params: 0\n",
      "__________________________________________________________________________________________________\n",
      "__________________________________________________________________________________________________\n",
      "Layer (type)                    Output Shape         Param #     Connected to                     \n",
      "==================================================================================================\n",
      "input_6 (InputLayer)            (None, 200, 200, 22) 0                                            \n",
      "__________________________________________________________________________________________________\n",
      "input_7 (InputLayer)            (None, 200, 200, 22) 0                                            \n",
      "__________________________________________________________________________________________________\n",
      "lambda_3 (Lambda)               (None, 200, 200, 22) 0           input_6[0][0]                    \n",
      "__________________________________________________________________________________________________\n",
      "lambda_14 (Lambda)              (None, 200, 200, 22) 0           input_7[0][0]                    \n",
      "__________________________________________________________________________________________________\n",
      "model_3 (Model)                 (None, 200, 200, 11) 446296      lambda_3[0][0]                   \n",
      "                                                                 input_7[0][0]                    \n",
      "                                                                 input_6[0][0]                    \n",
      "                                                                 lambda_14[0][0]                  \n",
      "                                                                 input_6[0][0]                    \n",
      "                                                                 lambda_18[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "lambda_6 (Lambda)               (None, 200, 200, 11) 0           input_6[0][0]                    \n",
      "__________________________________________________________________________________________________\n",
      "lambda_15 (Lambda)              (None, 200, 200, 11) 0           input_6[0][0]                    \n",
      "__________________________________________________________________________________________________\n",
      "lambda_18 (Lambda)              (None, 200, 200, 22) 0           input_7[0][0]                    \n",
      "__________________________________________________________________________________________________\n",
      "subtract_1 (Subtract)           (None, 200, 200, 11) 0           model_3[1][0]                    \n",
      "                                                                 lambda_6[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "lambda_7 (Lambda)               (None, 200, 200, 11) 0           input_7[0][0]                    \n",
      "__________________________________________________________________________________________________\n",
      "subtract_2 (Subtract)           (None, 200, 200, 11) 0           lambda_15[0][0]                  \n",
      "                                                                 model_3[2][0]                    \n",
      "__________________________________________________________________________________________________\n",
      "lambda_16 (Lambda)              (None, 200, 200, 11) 0           input_7[0][0]                    \n",
      "__________________________________________________________________________________________________\n",
      "lambda_19 (Lambda)              (None, 200, 200, 11) 0           input_6[0][0]                    \n",
      "__________________________________________________________________________________________________\n",
      "multiply_21 (Multiply)          (None, 200, 200, 11) 0           subtract_1[0][0]                 \n",
      "                                                                 lambda_7[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "multiply_23 (Multiply)          (None, 200, 200, 11) 0           subtract_2[0][0]                 \n",
      "                                                                 lambda_16[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "subtract_3 (Subtract)           (None, 200, 200, 11) 0           model_3[3][0]                    \n",
      "                                                                 lambda_19[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "lambda_20 (Lambda)              (None, 200, 200, 11) 0           input_7[0][0]                    \n",
      "__________________________________________________________________________________________________\n",
      "multiply_22 (Multiply)          (None, 200, 200, 11) 0           multiply_21[0][0]                \n",
      "                                                                 multiply_21[0][0]                \n",
      "__________________________________________________________________________________________________\n",
      "multiply_24 (Multiply)          (None, 200, 200, 11) 0           multiply_23[0][0]                \n",
      "                                                                 multiply_23[0][0]                \n",
      "__________________________________________________________________________________________________\n",
      "multiply_25 (Multiply)          (None, 200, 200, 11) 0           subtract_3[0][0]                 \n",
      "                                                                 lambda_20[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "reshape_1 (Reshape)             (None, Dimension(200 0           multiply_22[0][0]                \n",
      "__________________________________________________________________________________________________\n",
      "reshape_3 (Reshape)             (None, Dimension(200 0           multiply_24[0][0]                \n",
      "__________________________________________________________________________________________________\n",
      "multiply_26 (Multiply)          (None, 200, 200, 11) 0           multiply_25[0][0]                \n",
      "                                                                 multiply_25[0][0]                \n",
      "__________________________________________________________________________________________________\n",
      "global_average_pooling3d_1 (Glo (None, 1)            0           reshape_1[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "global_average_pooling3d_2 (Glo (None, 1)            0           reshape_3[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "reshape_5 (Reshape)             (None, Dimension(200 0           multiply_26[0][0]                \n",
      "__________________________________________________________________________________________________\n",
      "reshape_2 (Reshape)             (None, 1)            0           global_average_pooling3d_1[0][0] \n",
      "__________________________________________________________________________________________________\n",
      "reshape_4 (Reshape)             (None, 1)            0           global_average_pooling3d_2[0][0] \n",
      "__________________________________________________________________________________________________\n",
      "global_average_pooling3d_3 (Glo (None, 1)            0           reshape_5[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "lambda_8 (Lambda)               (None, 1)            0           reshape_2[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "lambda_17 (Lambda)              (None, 1)            0           reshape_4[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "reshape_6 (Reshape)             (None, 1)            0           global_average_pooling3d_3[0][0] \n",
      "__________________________________________________________________________________________________\n",
      "add_41 (Add)                    (None, 1)            0           lambda_8[0][0]                   \n",
      "                                                                 lambda_17[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "lambda_21 (Lambda)              (None, 1)            0           reshape_6[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "add_42 (Add)                    (None, 1)            0           add_41[0][0]                     \n",
      "                                                                 lambda_21[0][0]                  \n",
      "==================================================================================================\n",
      "Total params: 446,296\n",
      "Trainable params: 446,296\n",
      "Non-trainable params: 0\n",
      "__________________________________________________________________________________________________\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(11, 11, 22, 40)\n",
      "Train on 247 samples, validate on 28 samples\n",
      "Epoch 1/20\n",
      "247/247 [==============================] - 19s 77ms/step - loss: 0.1115 - add_42_loss: 0.0103 - model_3_loss: 0.1012 - val_loss: 0.0995 - val_add_42_loss: 0.0091 - val_model_3_loss: 0.0903\n",
      "Epoch 2/20\n",
      "247/247 [==============================] - 14s 57ms/step - loss: 0.1085 - add_42_loss: 0.0098 - model_3_loss: 0.0987 - val_loss: 0.0947 - val_add_42_loss: 0.0078 - val_model_3_loss: 0.0869\n",
      "Epoch 3/20\n",
      "247/247 [==============================] - 14s 57ms/step - loss: 0.1021 - add_42_loss: 0.0081 - model_3_loss: 0.0940 - val_loss: 0.0862 - val_add_42_loss: 0.0057 - val_model_3_loss: 0.0805\n",
      "Epoch 4/20\n",
      "247/247 [==============================] - 14s 57ms/step - loss: 0.0946 - add_42_loss: 0.0064 - model_3_loss: 0.0882 - val_loss: 0.0804 - val_add_42_loss: 0.0047 - val_model_3_loss: 0.0757\n",
      "Epoch 5/20\n",
      "247/247 [==============================] - 14s 57ms/step - loss: 0.0888 - add_42_loss: 0.0054 - model_3_loss: 0.0834 - val_loss: 0.0743 - val_add_42_loss: 0.0037 - val_model_3_loss: 0.0707\n",
      "Epoch 6/20\n",
      "247/247 [==============================] - 14s 57ms/step - loss: 0.0836 - add_42_loss: 0.0045 - model_3_loss: 0.0790 - val_loss: 0.0706 - val_add_42_loss: 0.0032 - val_model_3_loss: 0.0674\n",
      "Epoch 7/20\n",
      "247/247 [==============================] - 14s 58ms/step - loss: 0.0804 - add_42_loss: 0.0041 - model_3_loss: 0.0763 - val_loss: 0.0677 - val_add_42_loss: 0.0029 - val_model_3_loss: 0.0648\n",
      "Epoch 8/20\n",
      "247/247 [==============================] - 14s 57ms/step - loss: 0.0778 - add_42_loss: 0.0038 - model_3_loss: 0.0741 - val_loss: 0.0650 - val_add_42_loss: 0.0026 - val_model_3_loss: 0.0624\n",
      "Epoch 9/20\n",
      "247/247 [==============================] - 14s 58ms/step - loss: 0.0746 - add_42_loss: 0.0034 - model_3_loss: 0.0712 - val_loss: 0.0610 - val_add_42_loss: 0.0023 - val_model_3_loss: 0.0588\n",
      "Epoch 10/20\n",
      "247/247 [==============================] - 14s 57ms/step - loss: 0.0709 - add_42_loss: 0.0031 - model_3_loss: 0.0678 - val_loss: 0.0570 - val_add_42_loss: 0.0020 - val_model_3_loss: 0.0551\n",
      "Epoch 11/20\n",
      "247/247 [==============================] - 14s 58ms/step - loss: 0.0672 - add_42_loss: 0.0028 - model_3_loss: 0.0644 - val_loss: 0.0535 - val_add_42_loss: 0.0017 - val_model_3_loss: 0.0518\n",
      "Epoch 12/20\n",
      "247/247 [==============================] - 14s 58ms/step - loss: 0.0639 - add_42_loss: 0.0025 - model_3_loss: 0.0613 - val_loss: 0.0500 - val_add_42_loss: 0.0015 - val_model_3_loss: 0.0484\n",
      "Epoch 13/20\n",
      "247/247 [==============================] - 14s 57ms/step - loss: 0.0608 - add_42_loss: 0.0023 - model_3_loss: 0.0585 - val_loss: 0.0470 - val_add_42_loss: 0.0014 - val_model_3_loss: 0.0456\n",
      "Epoch 14/20\n",
      "247/247 [==============================] - 14s 58ms/step - loss: 0.0580 - add_42_loss: 0.0022 - model_3_loss: 0.0559 - val_loss: 0.0442 - val_add_42_loss: 0.0013 - val_model_3_loss: 0.0430\n",
      "Epoch 15/20\n",
      "247/247 [==============================] - 15s 60ms/step - loss: 0.0559 - add_42_loss: 0.0020 - model_3_loss: 0.0538 - val_loss: 0.0422 - val_add_42_loss: 0.0011 - val_model_3_loss: 0.0410\n",
      "Epoch 16/20\n",
      "247/247 [==============================] - 15s 60ms/step - loss: 0.0541 - add_42_loss: 0.0020 - model_3_loss: 0.0522 - val_loss: 0.0405 - val_add_42_loss: 0.0011 - val_model_3_loss: 0.0394\n",
      "Epoch 17/20\n",
      "247/247 [==============================] - 15s 60ms/step - loss: 0.0526 - add_42_loss: 0.0019 - model_3_loss: 0.0507 - val_loss: 0.0391 - val_add_42_loss: 0.0010 - val_model_3_loss: 0.0381\n",
      "Epoch 18/20\n",
      "247/247 [==============================] - 14s 59ms/step - loss: 0.0515 - add_42_loss: 0.0018 - model_3_loss: 0.0496 - val_loss: 0.0382 - val_add_42_loss: 0.0010 - val_model_3_loss: 0.0372\n",
      "Epoch 19/20\n",
      "247/247 [==============================] - 14s 58ms/step - loss: 0.0506 - add_42_loss: 0.0018 - model_3_loss: 0.0488 - val_loss: 0.0374 - val_add_42_loss: 9.6570e-04 - val_model_3_loss: 0.0364\n",
      "Epoch 20/20\n",
      "247/247 [==============================] - 14s 58ms/step - loss: 0.0498 - add_42_loss: 0.0017 - model_3_loss: 0.0481 - val_loss: 0.0367 - val_add_42_loss: 9.2046e-04 - val_model_3_loss: 0.0358\n",
      ".................. Encoder .modelNATL60_SSH_275_200_200_dW000WFilter011_NFilter040_RU010_LR004woSR_Alpha100_AE02D40N03W04_Nproj00_Encoder_iter000.mod\n",
      ".................. Decoder .modelNATL60_SSH_275_200_200_dW000WFilter011_NFilter040_RU010_LR004woSR_Alpha100_AE02D40N03W04_Nproj00_Decoder_iter000.mod\n",
      "Train on 247 samples, validate on 28 samples\n",
      "Epoch 1/20\n",
      "247/247 [==============================] - 14s 57ms/step - loss: 0.0493 - add_42_loss: 0.0017 - model_3_loss: 0.0476 - val_loss: 0.0362 - val_add_42_loss: 9.0469e-04 - val_model_3_loss: 0.0353\n",
      "Epoch 2/20\n",
      "184/247 [=====================>........] - ETA: 3s - loss: 0.0490 - add_42_loss: 0.0017 - model_3_loss: 0.0473"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "distributed.nanny - WARNING - Restarting worker\n",
      "distributed.nanny - ERROR - Failed to restart worker after its process exited\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/nanny.py\", line 291, in _on_exit\n",
      "    yield self.instantiate()\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/tornado/gen.py\", line 1133, in run\n",
      "    value = future.result()\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/asyncio/futures.py\", line 294, in result\n",
      "    raise self._exception\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/tornado/gen.py\", line 1141, in run\n",
      "    yielded = self.gen.throw(*exc_info)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/nanny.py\", line 226, in instantiate\n",
      "    self.process.start()\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/tornado/gen.py\", line 1133, in run\n",
      "    value = future.result()\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/asyncio/futures.py\", line 294, in result\n",
      "    raise self._exception\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/tornado/gen.py\", line 1141, in run\n",
      "    yielded = self.gen.throw(*exc_info)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/nanny.py\", line 370, in start\n",
      "    yield self.process.start()\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/tornado/gen.py\", line 1133, in run\n",
      "    value = future.result()\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/asyncio/futures.py\", line 294, in result\n",
      "    raise self._exception\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 184, in _start\n",
      "    process.start()\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 105, in start\n",
      "    self._popen = self._Popen(self)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/context.py\", line 281, in _Popen\n",
      "    return Popen(process_obj)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/popen_forkserver.py\", line 36, in __init__\n",
      "    super().__init__(process_obj)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/popen_fork.py\", line 20, in __init__\n",
      "    self._launch(process_obj)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/popen_forkserver.py\", line 52, in _launch\n",
      "    self.sentinel, w = forkserver.connect_to_new_process(self._fds)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/forkserver.py\", line 66, in connect_to_new_process\n",
      "    client.connect(self._forkserver_address)\n",
      "ConnectionRefusedError: [Errno 111] Connection refused\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n"
     ]
    },
    {
     "ename": "KeyboardInterrupt",
     "evalue": "",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-8-226df7bb0c52>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mFP_solver\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mglobParams\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mgenFilename\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mx_train\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mmask_train\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mgt_train\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mmeanTr\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mstdTr\u001b[0m\u001b[0;34m,\u001b[0m          \u001b[0mx_test\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mmask_test\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mgt_test\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mlday_test\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mx_train_OI\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mx_test_OI\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mencoder\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mdecoder\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mmodel_AE\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mDIMCAE\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;32m/data/home/AI4OAC-VM8/2020a_IMT_SSH_mapping_NATL60/DINAE/mods/FP_solver.py\u001b[0m in \u001b[0;36mFP_solver\u001b[0;34m(dict_global_Params, genFilename, x_train, mask_train, gt_train, meanTr, stdTr, x_test, mask_test, gt_test, lday_test, x_train_OI, x_test_OI, encoder, decoder, model_AE, DimCAE)\u001b[0m\n\u001b[1;32m     63\u001b[0m                   \u001b[0mepochs\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mNbEpoc\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     64\u001b[0m                   \u001b[0mverbose\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;36m1\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 65\u001b[0;31m                   validation_split=val_split)\n\u001b[0m\u001b[1;32m     66\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     67\u001b[0m         \u001b[0;31m# *********************** #\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/anaconda/envs/py35/lib/python3.5/site-packages/keras/engine/training.py\u001b[0m in \u001b[0;36mfit\u001b[0;34m(self, x, y, batch_size, epochs, verbose, callbacks, validation_split, validation_data, shuffle, class_weight, sample_weight, initial_epoch, steps_per_epoch, validation_steps, **kwargs)\u001b[0m\n\u001b[1;32m   1035\u001b[0m                                         \u001b[0minitial_epoch\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0minitial_epoch\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1036\u001b[0m                                         \u001b[0msteps_per_epoch\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0msteps_per_epoch\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1037\u001b[0;31m                                         validation_steps=validation_steps)\n\u001b[0m\u001b[1;32m   1038\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1039\u001b[0m     def evaluate(self, x=None, y=None,\n",
      "\u001b[0;32m/anaconda/envs/py35/lib/python3.5/site-packages/keras/engine/training_arrays.py\u001b[0m in \u001b[0;36mfit_loop\u001b[0;34m(model, f, ins, out_labels, batch_size, epochs, verbose, callbacks, val_f, val_ins, shuffle, callback_metrics, initial_epoch, steps_per_epoch, validation_steps)\u001b[0m\n\u001b[1;32m    197\u001b[0m                     \u001b[0mins_batch\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mi\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mins_batch\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mi\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtoarray\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    198\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 199\u001b[0;31m                 \u001b[0mouts\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mf\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mins_batch\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    200\u001b[0m                 \u001b[0mouts\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mto_list\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mouts\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    201\u001b[0m                 \u001b[0;32mfor\u001b[0m \u001b[0ml\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mo\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mzip\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mout_labels\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mouts\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/anaconda/envs/py35/lib/python3.5/site-packages/keras/backend/tensorflow_backend.py\u001b[0m in \u001b[0;36m__call__\u001b[0;34m(self, inputs)\u001b[0m\n\u001b[1;32m   2664\u001b[0m                 \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_legacy_call\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0minputs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2665\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2666\u001b[0;31m             \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_call\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0minputs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   2667\u001b[0m         \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2668\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mpy_any\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mis_tensor\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mx\u001b[0m \u001b[0;32min\u001b[0m \u001b[0minputs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/anaconda/envs/py35/lib/python3.5/site-packages/keras/backend/tensorflow_backend.py\u001b[0m in \u001b[0;36m_call\u001b[0;34m(self, inputs)\u001b[0m\n\u001b[1;32m   2634\u001b[0m                                 \u001b[0msymbol_vals\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2635\u001b[0m                                 session)\n\u001b[0;32m-> 2636\u001b[0;31m         \u001b[0mfetched\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_callable_fn\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0marray_vals\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   2637\u001b[0m         \u001b[0;32mreturn\u001b[0m \u001b[0mfetched\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0moutputs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2638\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/anaconda/envs/py35/lib/python3.5/site-packages/tensorflow/python/client/session.py\u001b[0m in \u001b[0;36m__call__\u001b[0;34m(self, *args)\u001b[0m\n\u001b[1;32m   1449\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_session\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_created_with_new_api\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1450\u001b[0m           return tf_session.TF_SessionRunCallable(\n\u001b[0;32m-> 1451\u001b[0;31m               self._session._session, self._handle, args, status, None)\n\u001b[0m\u001b[1;32m   1452\u001b[0m         \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1453\u001b[0m           return tf_session.TF_DeprecatedSessionRunCallable(\n",
      "\u001b[0;31mKeyboardInterrupt\u001b[0m: "
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
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      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
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      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
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     ]
    }
   ],
   "source": [
    "FP_solver(globParams,genFilename,x_train,mask_train,gt_train,meanTr,stdTr,\\\n",
    "          x_test,mask_test,gt_test,lday_test,x_train_OI,x_test_OI,encoder,decoder,model_AE,DIMCAE)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 5 - POSTPROCESSING"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 5.1 Plot figures    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. RestartingFuture exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 2880x1800 with 6 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
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      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
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      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "Future exception was never retrieved\n",
      "future: <Future finished exception=AttributeError(\"'NoneType' object has no attribute 'terminate'\",)>\n",
      "Traceback (most recent call last):\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/site-packages/distributed/process.py\", line 35, in _call_and_set_future\n",
      "    res = func(*args, **kwargs)\n",
      "  File \"/anaconda/envs/py35/lib/python3.5/multiprocessing/process.py\", line 116, in terminate\n",
      "    self._popen.terminate()\n",
      "AttributeError: 'NoneType' object has no attribute 'terminate'\n",
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
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     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "distributed.nanny - WARNING - Worker exceeded 95% memory budget. Restarting\n",
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     ]
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "from utils.plot_maps import *\n",
    "from utils.fourier_spectra import *\n",
    "from utils.export_NetCDF import *\n",
    "\n",
    "# get lon, lat and extent \n",
    "lon = xr.open_dataset(\"ref.nc\").lon.values[:200]\n",
    "lat = xr.open_dataset(\"ref.nc\").lat.values[:200]\n",
    "indN_Tt = np.concatenate([np.arange(60,80),np.arange(140,160),\\\n",
    "                             np.arange(220,240),np.arange(300,320)])  # index of evaluation period\n",
    "indN_Tr = np.delete(range(365),indN_Tt)                               # index of training period\n",
    "#indN_Tt = np.arange(start_eval_index,end_eval_index)   # index of evaluation period\n",
    "#indN_Tr = np.arange(start_train_index,end_train_index) # index of training period\n",
    "time = xr.open_dataset(\"ref.nc\").time.values[indN_Tt]\n",
    "extent = [np.min(lon),np.max(lon),np.min(lat),np.max(lat)]\n",
    "\n",
    "# read the reference NetCDF file\n",
    "GT = xr.open_dataset(\"ref.nc\").ssh.values[indN_Tt]\n",
    "# read the oi NetCDF file\n",
    "itrp_OI = xr.open_dataset(\"oi.nc\").ssh_mod.values[indN_Tt]\n",
    "# export the itrp pickle file as NetCDF\n",
    "ifile='saved_path_'+str(Niter-1).zfill(3)+'_FP_GENN_wmissing.pickle'\n",
    "ifile='saved_path_000_FP_GENN_wwmissing.pickle'\n",
    "ofile='FP_GENN.nc'\n",
    "export_NetCDF(ifile,ofile,lon,lat,time)\n",
    "# read the itrp NetCDF file\n",
    "itrp_FP_GENN = xr.open_dataset(\"FP_GENN.nc\").FP_GENN.values\n",
    "\n",
    "i = 50 # index of the evaluation day to plot\n",
    "gt           = GT[i,:200,:200]\n",
    "Grad_gt      = Gradient(gt,2)\n",
    "OI          = itrp_OI[i,:200,:200]\n",
    "Grad_OI      = Gradient(OI,2)\n",
    "FP_GENN      = itrp_FP_GENN[i,:200,:200]\n",
    "Grad_FP_GENN = Gradient(FP_GENN,2)\n",
    "\n",
    "fig, ax = plt.subplots(1,3,figsize=(40,25),squeeze=False,\n",
    "                        subplot_kw=dict(projection=ccrs.PlateCarree(central_longitude=0.0)))\n",
    "\n",
    "vmin = np.nanmin(Grad_gt) ; vmax = np.nanmax(Grad_gt)\n",
    "cmap=\"viridis\"\n",
    "plot(ax,0,0,lon,lat,Grad_gt, r\"$\\nabla_{GT}$\",\\\n",
    "             extent=extent,cmap=cmap,vmin=vmin,vmax=vmax)\n",
    "plot(ax,0,1,lon,lat,Grad_OI, r\"$\\nabla_{OI}$\",\\\n",
    "             extent=extent,cmap=cmap,vmin=vmin,vmax=vmax)\n",
    "plot(ax,0,2,lon,lat,Grad_FP_GENN, r\"$\\nabla_{FP-GENN}$\",\\\n",
    "             extent=extent,cmap=cmap,vmin=vmin,vmax=vmax)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 5.2 Compute RMSE and spectrum   "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "nrmse_OI=np.zeros(len(GT))\n",
    "nrmse_FP_GENN=np.zeros(len(GT))\n",
    "\n",
    "for i in range(0,len(GT)):\n",
    "    gt           = GT[i,:200,:200]\n",
    "    OI_          = itrp_OI[i,:200,:200]\n",
    "    FP_GENN      = itrp_FP_GENN[i,:200,:200]\n",
    "    nrmse_OI[i]      =  (np.sqrt(np.nanmean(((gt-np.nanmean(gt))-(OI-np.nanmean(OI)))**2)))/np.nanstd(gt)\n",
    "    nrmse_FP_GENN[i] =  (np.sqrt(np.nanmean(((gt-np.nanmean(gt))-(FP_GENN-np.nanmean(FP_GENN)))**2)))/np.nanstd(gt)\n",
    "    \n",
    "# plot nRMSE time series\n",
    "N=len(GT)\n",
    "plt.plot(range(N),nrmse_OI,linestyle='solid',color='red',linewidth=2,label=r\"$OI$\")\n",
    "plt.plot(range(N),nrmse_FP_GENN,linestyle='solid',color='seagreen',linewidth=1,label=r\"$FP_GENN$\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "../utils/fourier_spectra.py:101: RuntimeWarning: invalid value encountered in true_divide\n",
      "  Pf_     = (Pf_/raPsd2dv1(img2,res,hanning)[1])\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot averaged normalize error RAPS \n",
    "f0, Pf_OI        = avg_err_raPsd2dv1(itrp_OI[:,:200,:200],GT[:,:200,:200],4,True)\n",
    "f1, Pf_FP_GENN   = avg_err_raPsd2dv1(itrp_FP_GENN[:,:200,:200],GT[:,:200,:200],4,True)\n",
    "wf0 = 1/f0\n",
    "wf1 = 1/f1\n",
    "fig = plt.figure()\n",
    "ax = fig.add_subplot(111)\n",
    "ax.plot(wf0[1:],Pf_OI[1:],linestyle='solid',color='red',linewidth=.5,label='OI')\n",
    "ax.plot(wf1[1:],Pf_FP_GENN[1:],linestyle='solid',color='seagreen',linewidth=.5,label='FP-GENN')\n",
    "ax.set_xlabel(\"Wavenumber\", fontweight='bold')\n",
    "ax.set_ylabel(\"Power spectral density (m2/(cy/km))\", fontweight='bold')\n",
    "ax.set_xscale('log') ; ax.set_yscale('log')\n",
    "plt.legend(loc='best',prop=dict(size='small'),frameon=False)\n",
    "plt.xticks([50, 100, 200, 500, 1000], [\"50km\", \"100km\", \"200km\", \"500km\", \"1000km\"])\n",
    "ax.invert_xaxis()\n",
    "plt.grid(which='both', linestyle='--')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3.5",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.5.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
